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\n \n 2021\n \n \n (6)\n \n \n

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\n \n\n \n \n \n \n \n \n Train Route Planning as a Multi-agent Path Finding Problem.\n \n \n \n \n\n\n \n Salerno, M.; Martín, Y. E.; Fuentetaja, R.; Gragera, A.; Pozanco, A.; and Borrajo, D.\n\n\n \n\n\n\n In Alba, E.; Luque, G.; Chicano, F.; Cotta, C.; Camacho, D.; Ojeda-Aciego, M.; Montes, S.; Troncoso, A.; Riquelme, J. C.; and Gil-Merino, R., editor(s), Advances in Artificial Intelligence - 19th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2020/2021, Málaga, Spain, September 22-24, 2021, Proceedings, volume 12882, of Lecture Notes in Computer Science, pages 237–246, 2021. Springer\n \n\n\n\n
\n\n\n\n \n \n $\"Train$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{DBLP:conf/caepia/SalernoMFGPB21,\n  author    = {Mauricio Salerno and\n               Yolanda Escudero Mart{\\'{\\i}}n and\n               Raquel Fuentetaja and\n               Alba Gragera and\n               Alberto Pozanco and\n               Daniel Borrajo},\n  editor    = {Enrique Alba and\n               Gabriel Luque and\n               Francisco Chicano and\n               Carlos Cotta and\n               David Camacho and\n               Manuel Ojeda{-}Aciego and\n               Susana Montes and\n               Alicia Troncoso and\n               Jos{\\'{e}} C. Riquelme and\n               Rodrigo Gil{-}Merino},\n  title     = {Train Route Planning as a Multi-agent Path Finding Problem},\n  booktitle = {Advances in Artificial Intelligence - 19th Conference of the Spanish\n               Association for Artificial Intelligence, {CAEPIA} 2020/2021, M{\\'{a}}laga,\n               Spain, September 22-24, 2021, Proceedings},\n  series    = {Lecture Notes in Computer Science},\n  volume    = {12882},\n  pages     = {237--246},\n  publisher = {Springer},\n  year      = {2021},\n  url       = {https://doi.org/10.1007/978-3-030-85713-4\\_23},\n  doi       = {10.1007/978-3-030-85713-4\\_23},\n  timestamp = {Tue, 14 Sep 2021 19:09:32 +0200},\n  biburl    = {https://dblp.org/rec/conf/caepia/SalernoMFGPB21.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Model and Graphical Tool to Formalize Human-Robot Interaction Based on Automated Planning.\n \n \n \n\n\n \n Gragera, A.; García-Olaya, Angel; Fernández, F.; and Marfil, R.\n\n\n \n\n\n\n In Proceedings of International Conference on Automated Planning and Scheduling. System Demonstrations and Exhibits, 2021. \n \n\n\n\n
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@inProceedings{gragera2021model,\n  author    = {Gragera, Alba and Garc{\\'i}a-Olaya, Angel and Fern{\\'a}ndez, Fernando and Marfil, Rebeca},\n  title     = {Model and Graphical Tool to Formalize Human-Robot Interaction Based on Automated Planning},\n  booktitle = {Proceedings of International Conference on Automated Planning and Scheduling. System Demonstrations and Exhibits},\n  year      = {2021}\n}\n\n

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\n \n\n \n \n \n \n \n \n Selecting goals in oversubscription planning using relaxed plans.\n \n \n \n \n\n\n \n García-Olaya, A.; de la Rosa, T.; and Borrajo, D.\n\n\n \n\n\n\n Artificial Intelligence, 291: 103414. feb 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Selecting$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Garcia-Olaya2021,\nauthor = {Garc{\\'{i}}a-Olaya, Angel and de la Rosa, Tom{\\'{a}}s and Borrajo, Daniel},\ndoi = {10.1016/j.artint.2020.103414},\nissn = {00043702},\njournal = {Artificial Intelligence},\nmonth = {feb},\npages = {103414},\npublisher = {Elsevier B.V.},\ntitle = {{Selecting goals in oversubscription planning using relaxed plans}},\nurl = {https://doi.org/10.1016/j.artint.2020.103414 https://linkinghub.elsevier.com/retrieve/pii/S0004370220301636},\nvolume = {291},\nyear = {2021}\n}\n\n

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\n \n\n \n \n \n \n \n Advising Agent for Service-Providing Live-Chat Operators.\n \n \n \n\n\n \n Aviv, A.; Oshrat, Y.; Assefa, S. A.; Mustapha, T.; Borrajo, D.; Veloso, M.; and Kraus, S.\n\n\n \n\n\n\n arXiv e-prints, abs/2105.03986. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@Article{arxiv21-advising,\n      title={Advising Agent for Service-Providing Live-Chat Operators},\n      author={Aviram Aviv and Yaniv Oshrat and Samuel A. Assefa and Tobi Mustapha and Daniel Borrajo and Manuela Veloso\n                  and Sarit Kraus},\n      year={2021},\n      journal   = {arXiv e-prints},\n      volume    = {abs/2105.03986},\n      primaryClass={cs.CL}\n}\n\n

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\n \n\n \n \n \n \n \n \n Computing Opportunities to Augment Plans for Novel Replanning during Execution.\n \n \n \n \n\n\n \n Borrajo, D.; and Veloso, M.\n\n\n \n\n\n\n In Proceedings of ICAPS'21, Guangzhou (China), 2021. \n Accepted\n\n\n\n
\n\n\n\n \n \n $\"Computing$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{icaps21-opportunities,\n  author = {Daniel Borrajo and Manuela Veloso},\n  title =      {Computing Opportunities to Augment Plans for Novel Replanning during Execution},\n  booktitle =      {Proceedings of ICAPS'21},\n  OPTcrossref =  {},\n  key =         {Planning-Learning},\n  cicyt =     {congresos-buenos},\n  jcr =         {A*},\n  url =          {},\n  OPTeditor =      {},\n  OPTvolume =      {},\n  OPTnumber =      {},\n  OPTseries =      {},\n  year =     {2021},\n  OPTorganization = {},\n  OPTpublisher = {},\n  address =     {Guangzhou (China)},\n  OPTmonth =      {},\n  pages =     {},\n  note =     {Accepted},\n  OPTannote =      {Short paper}\n}\n\n

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\n \n\n \n \n \n \n \n \n Disturbing Reinforcement Learning Agents with Corrupted Rewards.\n \n \n \n \n\n\n \n Majadas, R.; García, J.; and Fernández, F.\n\n\n \n\n\n\n CoRR, abs/2102.06587. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Disturbing$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{DBLP:journals/corr/abs-2102-06587,\n  author    = {Rub{\\'{e}}n Majadas and\n               Javier Garc{\\'{\\i}}a and\n               Fernando Fern{\\'{a}}ndez},\n  title     = {Disturbing Reinforcement Learning Agents with Corrupted Rewards},\n  journal   = {CoRR},\n  volume    = {abs/2102.06587},\n  year      = {2021},\n  url       = {https://arxiv.org/abs/2102.06587},\n  archivePrefix = {arXiv},\n  eprint    = {2102.06587},\n  timestamp = {Thu, 18 Feb 2021 15:26:00 +0100},\n  biburl    = {https://dblp.org/rec/journals/corr/abs-2102-06587.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n

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\n \n 2020\n \n \n (11)\n \n \n

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\n \n\n \n \n \n \n \n Supporting the Formalization of Use Cases in Social Robotics.\n \n \n \n\n\n \n Gragera, A.; García-Olaya, Angel; and Fernández, F.\n\n\n \n\n\n\n In Proceedings of Workshop on Knowledge Engineering for Planning and Scheduling, ICAPS'20, 2020. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inProceedings{gragerasupporting,\n  author    = {Gragera, Alba and Garc{\\'i}a-Olaya, Angel and Fern{\\'a}ndez, Fernando},\n  title\t    = {Supporting the Formalization of Use Cases in Social Robotics},\n  booktitle = {Proceedings of Workshop on Knowledge Engineering for Planning and Scheduling, ICAPS'20},\n  year      = {2020}\n}\n\n

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\n \n\n \n \n \n \n \n Goal Recognition via Model-based and Model-free Techniques.\n \n \n \n\n\n \n Borrajo, D.; Gopalakrishnan, S.; and Potluru, V. K.\n\n\n \n\n\n\n In Preprints of the ICAPS Workshop on Planning for Financial Services (FinPlan), Nancy (France), 2020. \n Also in: https://arxiv.org/abs/2011.01832\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{finplan-gr,\n  author = {Daniel Borrajo and Sriram Gopalakrishnan and Vamsi K. Potluru},\n  title =  {Goal Recognition via Model-based and Model-free Techniques},\n  booktitle = {Preprints of the ICAPS Workshop on Planning for Financial Services (FinPlan)},\n  OPTcrossref =  {},\n  key =         {Planning-Learning},\n  cicyt =     {workshops},\n  jcr =         {},\n  OPTeditor =      {},\n  OPTvolume =      {},\n  OPTnumber =      {},\n  OPTseries =      {},\n  year =     {2020},\n  OPTorganization = {},\n  OPTpublisher = {},\n  address =     {Nancy (France)},\n  OPTmonth =      {},\n  OPTpages =      {},\n  note =     {Also in: https://arxiv.org/abs/2011.01832},\n  OPTannote =      {}\n}\n\n

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\n \n\n \n \n \n \n \n \n Goal recognition via model-based and model-free techniques.\n \n \n \n \n\n\n \n Borrajo, D.; Gopalakrishnan, S.; and Potluru, V. K.\n\n\n \n\n\n\n arXiv e-prints, abs/2011.01832. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Goal$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{arxiv-finplan-gr,\n  author    = {Daniel Borrajo and Sriram Gopalakrishnan and Vamsi K. Potluru},\n  title     = {Goal recognition via model-based and model-free techniques},\n  journal   = {arXiv e-prints},\n  volume    = {abs/2011.01832},\n  year      = {2020},\n  url       = {https://arxiv.org/abs/2011.01832},\n  archivePrefix = {arXiv},\n  eprint    = {2011.01832}\n}\n\n

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\n \n\n \n \n \n \n \n Domain-independent Generation and Classification of Behavior Traces.\n \n \n \n\n\n \n Borrajo, D.; and Veloso, M.\n\n\n \n\n\n\n In Preprints of the ICAPS Workshop on Planning for Financial Services (FinPlan), Nancy (France), 2020. \n Also in: https://arxiv.org/abs/2011.02918\n\n\n\n
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@InProceedings{finplan-simulator,\n  author = {Daniel Borrajo and Manuela Veloso},\n  title =  {Domain-independent Generation and Classification of Behavior Traces},\n  booktitle = {Preprints of the ICAPS Workshop on Planning for Financial Services (FinPlan)},\n  OPTcrossref =  {},\n  key =         {Planning-Learning},\n  cicyt =     {workshops},\n  jcr =         {},\n  OPTeditor =      {},\n  OPTvolume =      {},\n  OPTnumber =      {},\n  OPTseries =      {},\n  year =     {2020},\n  OPTorganization = {},\n  OPTpublisher = {},\n  address =     {Nancy (France)},\n  OPTmonth =      {},\n  OPTpages =      {},\n  note =     {Also in: https://arxiv.org/abs/2011.02918},\n  OPTannote =      {}\n}\n\n

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\n \n\n \n \n \n \n \n \n Domain-independent generation and classification of behavior traces.\n \n \n \n \n\n\n \n Borrajo, D.; and Veloso, M.\n\n\n \n\n\n\n arXiv e-prints, abs/2011.02918. 2020.\n \n\n\n\n
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@article{arxiv-finplan-simulator,\n  author    = {Daniel Borrajo and Manuela Veloso},\n  title     = {Domain-independent generation and classification of behavior traces},\n  journal   = {arXiv e-prints},\n  volume    = {abs/2011.02918},\n  year      = {2020},\n  url       = {https://arxiv.org/abs/2011.02918},\n  archivePrefix = {arXiv},\n  eprint    = {2011.02918}\n}\n\n

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\n \n\n \n \n \n \n \n Simulating and Classifying Behavior in Adversarial Environments Based on Action-State Traces: An Application to Money Laundering.\n \n \n \n\n\n \n Borrajo, D.; Veloso, M.; and Shah, S.\n\n\n \n\n\n\n In Proceedings of the 2020 ACM International Conference on AI in Finance, New York (EEUU), 2020. \n Also in: https://arxiv.org/abs/2011.01826\n\n\n\n
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@InProceedings{icaif20,\n  author = {Daniel Borrajo and Manuela Veloso and Sameena Shah},\n  title =  {Simulating and Classifying Behavior in Adversarial\n                  Environments Based on Action-State Traces: An\n                  Application to Money Laundering},\n  booktitle =      {Proceedings of the 2020 ACM International Conference on AI in Finance},\n  OPTcrossref =  {},\n  key =         {Planning-Learning},\n  cicyt =     {congresos},\n  jcr =         {},\n  OPTeditor =      {Tucker Balch},\n  OPTvolume =      {},\n  OPTnumber =      {},\n  OPTseries =      {},\n  year =     {2020},\n  OPTorganization = {},\n  OPTpublisher = {},\n  address =     {New York (EEUU)},\n  OPTmonth =      {October},\n  OPTpages =      {},\n  note =     {Also in: https://arxiv.org/abs/2011.01826},\n  OPTnote =     {},\n  OPTannote =      {}\n}\n\n

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\n \n\n \n \n \n \n \n \n Simulating and classifying behavior in adversarial environments based on action-state traces: an application to money laundering.\n \n \n \n \n\n\n \n Borrajo, D.; Veloso, M.; and Shah, S.\n\n\n \n\n\n\n arXiv e-prints, abs/2011.01826. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Simulating$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{arxiv-icaif20,\n  author    = {Daniel Borrajo and Manuela Veloso and Sameena Shah},\n  title     = {Simulating and classifying behavior in adversarial environments based\n               on action-state traces: an application to money laundering},\n  journal   = {arXiv e-prints},\n  volume    = {abs/2011.01826},\n  year      = {2020},\n  url       = {https://arxiv.org/abs/2011.01826},\n  archivePrefix = {arXiv},\n  eprint    = {2011.01826}\n}\n\n

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\n \n\n \n \n \n \n \n \n Learning adversarial attack policies through multi-objective reinforcement learning.\n \n \n \n \n\n\n \n García, J.; Majadas, R.; and Fernández, F.\n\n\n \n\n\n\n Eng. Appl. Artif. Intell., 96: 104021. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{DBLP:journals/eaai/GarciaMF20,\n  author    = {Javier Garc{\\'{\\i}}a and\n               Rub{\\'{e}}n Majadas and\n               Fernando Fern{\\'{a}}ndez},\n  title     = {Learning adversarial attack policies through multi-objective reinforcement\n               learning},\n  journal   = {Eng. Appl. Artif. Intell.},\n  volume    = {96},\n  pages     = {104021},\n  year      = {2020},\n  url       = {https://doi.org/10.1016/j.engappai.2020.104021},\n  doi       = {10.1016/j.engappai.2020.104021},\n  timestamp = {Tue, 12 Jan 2021 14:42:45 +0100},\n  biburl    = {https://dblp.org/rec/journals/eaai/GarciaMF20.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n\n

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\n \n\n \n \n \n \n \n \n Multi-Tier Automated Planning for Adaptive Behavior.\n \n \n \n \n\n\n \n Ciolek, D. A.; D'Ippolito, N.; Pozanco, A.; and Sardiña, S.\n\n\n \n\n\n\n In Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling, Nancy, France, October 26-30, 2020, pages 66–74, 2020. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Multi-Tier$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{DBLP:conf/aips/CiolekDPS20,\n  author    = {Daniel Alfredo Ciolek and\n               Nicol{\\'{a}}s D'Ippolito and\n               Alberto Pozanco and\n               Sebastian Sardi{\\~{n}}a},\n  title     = {Multi-Tier Automated Planning for Adaptive Behavior},\n  booktitle = {Proceedings of the Thirtieth International Conference on Automated\n               Planning and Scheduling, Nancy, France, October 26-30, 2020},\n  pages     = {66--74},\n  publisher = {{AAAI} Press},\n  year      = {2020},\n  url       = {https://aaai.org/ojs/index.php/ICAPS/article/view/6646},\n  timestamp = {Thu, 06 Aug 2020 13:53:42 +0200},\n  biburl    = {https://dblp.org/rec/conf/aips/CiolekDPS20.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n

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\n \n\n \n \n \n \n \n \n Multi-tier Automated Planning for Adaptive Behavior (Extended Version).\n \n \n \n \n\n\n \n Ciolek, D. A.; D'Ippolito, N.; Pozanco, A.; and Sardiña, S.\n\n\n \n\n\n\n CoRR, abs/2002.12445. 2020.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2002-12445,\n  author    = {Daniel Alfredo Ciolek and\n               Nicol{\\'{a}}s D'Ippolito and\n               Alberto Pozanco and\n               Sebastian Sardi{\\~{n}}a},\n  title     = {Multi-tier Automated Planning for Adaptive Behavior (Extended Version)},\n  journal   = {CoRR},\n  volume    = {abs/2002.12445},\n  year      = {2020},\n  url       = {https://arxiv.org/abs/2002.12445},\n  archivePrefix = {arXiv},\n  eprint    = {2002.12445},\n  timestamp = {Thu, 06 Aug 2020 13:51:51 +0200},\n  biburl    = {https://dblp.org/rec/journals/corr/abs-2002-12445.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n\n

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\n \n\n \n \n \n \n \n Get me to Safety Escaping from Risks using Automated Planning.\n \n \n \n\n\n \n Pozanco, A.; E-Martín, Y.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of IntExGR Workshop, ICAPS'20, Nancy (France), 2020. \n \n\n\n\n
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@inproceedings{pozancorisks2020,\n  title={Get me to Safety Escaping from Risks using Automated Planning},\n  author={Alberto Pozanco and\n               Yolanda E{-}Mart{\\'{\\i}}n and\n               Susana Fern{\\'{a}}ndez and\n               Daniel Borrajo},\n  booktitle={Proceedings of IntExGR Workshop, ICAPS'20, Nancy (France)},\n  year={2020}\n}\n\n\n

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\n \n\n \n \n \n \n \n \n Challenges on the Application of Automated Planning for Comprehensive Geriatric Assessment Using an Autonomous Social Robot.\n \n \n \n \n\n\n \n García-Olaya, A.; Fuentetaja, R.; García-Polo, J.; González, J. C.; and Fernández, F.\n\n\n \n\n\n\n In Advances in Intelligent Systems and Computing, volume 855, pages 179–194. Springer International Publishing, 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Challenges$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@incollection{Garcia-Olaya2019,\nabstract = {{\\textcopyright} 2019, Springer Nature Switzerland AG. Comprehensive Geriatric Assessment is a medical procedure to evaluate the physical, social and psychological status of elder patients. One of its phases consists of performing different tests to the patient or relatives. In this paper we present the challenges to apply Automated Planning to control an autonomous robot helping the clinician to perform such tests. On the one hand the paper focuses on the modelling decisions taken, from an initial approach where each test was encoded using slightly different domains, to the final unified domain allowing any test to be represented. On the other hand, the paper deals with practical issues arisen when executing the plans. Preliminary tests performed with real users show that the proposed approach is able to seamlessly handle the patient-robot interaction in real time, recovering from unexpected events and adapting to the users' preferred input method, while being able to gather all the information needed by the clinician.},\nauthor = {Garc{\\'{i}}a-Olaya, Angel and Fuentetaja, Raquel and Garc{\\'{i}}a-Polo, Javier and Gonz{\\'{a}}lez, Jos{\\'{e}} Carlos and Fern{\\'{a}}ndez, Fernando},\nbooktitle = {Advances in Intelligent Systems and Computing},\ndoi = {10.1007/978-3-319-99885-5_13},\nisbn = {9783319998848},\nissn = {21945357},\nkeywords = {Automated Planning,Comprehensive Geriatric Assessment,Health-care robotics,Human-Robot Interaction,Planning and execution,Social Robotics},\npages = {179--194},\npublisher = {Springer International Publishing},\ntitle = {{Challenges on the Application of Automated Planning for Comprehensive Geriatric Assessment Using an Autonomous Social Robot}},\nurl = {http://link.springer.com/10.1007/978-3-319-99885-5_13},\nvolume = {855},\nyear = {2019}\n}\n\n

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\n \n\n \n \n \n \n \n \n Efficient Approaches for Multi-Agent Planning.\n \n \n \n \n\n\n \n Borrajo, D.; and Fernández, S.\n\n\n \n\n\n\n Knowledge and Information Systems, 58(2): 425–479. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Efficient$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@Article{kais-mapr,\n  author =      {Daniel Borrajo and Susana Fernández},\n  title =      {Efficient Approaches for Multi-Agent Planning},\n  journal =      {Knowledge and Information Systems},\n  year =      {2019},\n  key =          {Planning-Learning},\n  cicyt =        {revista},\n  jcr =          {Q2, 2017: 2.247 (49/132), Computer Science. Information Systems (56/148)},\n  publisher =    {Springer Nature},\n  url =          {https://doi.org/10.1007/s10115-018-1202-1},\n  OPTkey =      {},\n  volume =     {58},\n  number =     {2},\n  month =     {},\n  pages =     {425--479},\n  OPTisbn =      {Printed 0219-1377, On-line 5-018-1202-1},\n  note =     {},\n  OPTannote =      {15-12-2015. 20-12-2016.}\n}\n\n

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\n \n\n \n \n \n \n \n \n Error Analysis and Correction for Weighted A*'s Suboptimality.\n \n \n \n \n\n\n \n Holte, R. C.; Majadas, R.; Pozanco, A.; and Borrajo, D.\n\n\n \n\n\n\n In Surynek, P.; and Yeoh, W., editor(s), Proceedings of the Twelfth International Symposium on Combinatorial Search, SOCS 2019, Napa, California, 16-17 July 2019, pages 135–139, 2019. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Error$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{DBLP:conf/socs/HolteMPB19,\n  author    = {Robert C. Holte and\n               Rub{\\'{e}}n Majadas and\n               Alberto Pozanco and\n               Daniel Borrajo},\n  editor    = {Pavel Surynek and\n               William Yeoh},\n  title     = {Error Analysis and Correction for Weighted A*'s Suboptimality},\n  booktitle = {Proceedings of the Twelfth International Symposium on Combinatorial\n               Search, {SOCS} 2019, Napa, California, 16-17 July 2019},\n  pages     = {135--139},\n  publisher = {{AAAI} Press},\n  year      = {2019},\n  url       = {https://aaai.org/ocs/index.php/SOCS/SOCS19/paper/view/18338},\n  timestamp = {Wed, 10 Feb 2021 08:42:37 +0100},\n  biburl    = {https://dblp.org/rec/conf/socs/HolteMPB19.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Finding Centroids and Minimum Covering States in Planning.\n \n \n \n \n\n\n \n Pozanco, A.; E-Martín, Y.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling, ICAPS 2018, Berkeley, CA, USA, July 11-15, 2019, pages 348–352, 2019. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Finding$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 14 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{DBLP:conf/aips/PozancoEFB19,\n  author    = {Alberto Pozanco and\n               Yolanda E{-}Mart{\\'{\\i}}n and\n               Susana Fern{\\'{a}}ndez and\n               Daniel Borrajo},\n  title     = {Finding Centroids and Minimum Covering States in Planning},\n  booktitle = {Proceedings of the Twenty-Ninth International Conference on Automated\n               Planning and Scheduling, {ICAPS} 2018, Berkeley, CA, USA, July 11-15,\n               2019},\n  pages     = {348--352},\n  publisher = {{AAAI} Press},\n  year      = {2019},\n  url       = {https://aaai.org/ojs/index.php/ICAPS/article/view/3497},\n  timestamp = {Tue, 19 Nov 2019 08:03:24 +0100},\n  biburl    = {https://dblp.org/rec/conf/aips/PozancoEFB19.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n

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\n \n\n \n \n \n \n \n \n Insights from the 2018 IPC Benchmarks.\n \n \n \n \n\n\n \n Cenamor, I.; and Pozanco, A.\n\n\n \n\n\n\n In Proceedings of 5th Workshop on the International Planning Competition, ICAPS'19, Berkeley (USA), 2019. \n \n\n\n\n
\n\n\n\n \n \n $\"Insights$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{cenamor2019insights,\n  title={Insights from the 2018 IPC Benchmarks},\n  author={Isabel Cenamor and Alberto Pozanco},\n  booktitle={Proceedings of 5th Workshop on the International Planning Competition, ICAPS'19, Berkeley (USA)},\n  url={https://openreview.net/references/pdf?id=rkwXBesT4},\n  year={2019}\n}\n\n

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\n \n\n \n \n \n \n \n On-Line Case-Based Policy Learning for Automated Planning in Probabilistic Environments.\n \n \n \n\n\n \n Martínez, M.; García, J.; and Fernández, F.\n\n\n \n\n\n\n International Journal of Information Technology and Decision Making. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Martinez2018,\nabstract = {{\\textcopyright} 2018 World Scientific Publishing Company Many robotic control architectures perform a continuous cycle of sensing, reasoning and acting, where that reasoning can be carried out in a reactive or deliberative form. Reactive methods are fast and provide the robot with high interaction and response capabilities. Deliberative reasoning is particularly suitable in robotic systems because it employs some form of forward projection (reasoning in depth about goals, pre-conditions, resources and timing constraints) and provides the robot reasonable responses in situations unforeseen by the designer. However, this reasoning, typically conducted using Artificial Intelligence techniques like Automated Planning (AP), is not effective for controlling autonomous agents which operate in complex and dynamic environments. Deliberative planning, although feasible in stable situations, takes too long in unexpected or changing situations which require re-planning. Therefore, planning cannot be done on-line in many complex robotic problems, where quick responses are frequently required. In this paper, we propose an alternative approach based on case-based policy learning which integrates deliberative reasoning through AP and reactive response time through reactive planning policies. The method is based on learning planning knowledge from actual experiences to obtain a case-based policy. The contribution of this paper is two fold. First, it is shown that the learned case-based policy produces reasonable and timely responses in complex environments. Second, it is also shown how one case-based policy that solves a particular problem can be reused to solve a similar but more complex problem in a transfer learning scope.},\nauthor = {Mart{\\'{i}}nez, M. and Garc{\\'{i}}a, J. and Fern{\\'{a}}ndez, F.},\ndoi = {10.1142/S0219622018500086},\nissn = {02196220},\njournal = {International Journal of Information Technology and Decision Making},\nkeywords = {Automated planning,case-base reasoning,control systems,planning and execution,robotics},\ntitle = {{On-Line Case-Based Policy Learning for Automated Planning in Probabilistic Environments}},\nyear = {2018}\n}\n

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\n \n\n \n \n \n \n \n CLARC: A cognitive robot for helping geriatric doctors in real scenarios.\n \n \n \n\n\n \n Voilmy, D.; Suárez, C.; Romero-Garcés, A.; Reuther, C.; Pulido, J.; Marfil, R.; Manso, L.; Lan Hing Ting, K.; Iglesias, A.; González, J.; García, J.; García-Olaya, A.; Fuentetaja, R.; Fernández, F.; Dueñas, A.; Calderita, L.; Bustos, P.; Barile, T.; Bandera, J.; and Bandera, A.\n\n\n \n\n\n\n Volume 693 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

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@book{Voilmy2018,\nabstract = {{\\textcopyright} 2018, Springer International Publishing AG. Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate the frailty of elderly persons in order to create therapy plans that improve their quality of life. For robotizing these tests, we are designing and developing CLARC, a mobile robot able to help the physician to capture and manage data during the CGA procedures, mainly by autonomously conducting a set of predefined evaluation tests. Built around a shared internal representation of the outer world, the architecture is composed of software modules able to plan and generate a stream of actions, to execute actions emanated from the representation or to update this by including/removing items at different abstraction levels. Percepts, actions and intentions coming from all software modules are grounded within this unique representation. This allows the robot to react to unexpected events and to modify the course of action according to the dynamics of a scenario built around the interaction with the patient. The paper describes the architecture of the system as well as the preliminary user studies and evaluation to gather new user requirements.},\nauthor = {Voilmy, D. and Su{\\'{a}}rez, C. and Romero-Garc{\\'{e}}s, A. and Reuther, C. and Pulido, J.C. and Marfil, R. and Manso, L.J. and {Lan Hing Ting}, K. and Iglesias, A. and Gonz{\\'{a}}lez, J.C. and Garc{\\'{i}}a, J. and Garc{\\'{i}}a-Olaya, A. and Fuentetaja, R. and Fern{\\'{a}}ndez, F. and Due{\\~{n}}as, A. and Calderita, L.V. and Bustos, P. and Barile, T. and Bandera, J.P. and Bandera, A.},\nbooktitle = {Advances in Intelligent Systems and Computing},\ndoi = {10.1007/978-3-319-70833-1_33},\nissn = {21945357},\nkeywords = {Assistive robotics,Human-robot interaction},\ntitle = {{CLARC: A cognitive robot for helping geriatric doctors in real scenarios}},\nvolume = {693},\nyear = {2018}\n}\n

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\n \n\n \n \n \n \n \n LifeBots I: Building the software infrastructure for supporting lifelong technologies.\n \n \n \n\n\n \n Bandera, A.; Bandera, J.; Bustos, P.; Férnandez, F.; García-Olaya, A.; García-Polo, J.; García-Varea, I.; Manso, L.; Marfil, R.; Martínez-Gómez, J.; Núñez, P.; Perez-Lorenzo, J.; Reche-Lopez, P.; Romero-González, C.; and Viciana-Abad, R.\n\n\n \n\n\n\n Volume 693 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@book{Bandera2018,\nabstract = {{\\textcopyright} 2018, Springer International Publishing AG. The goal of the LifeBots project is the study and development of long-life mechanisms that facilitate and improve the integration of robotics platforms in smart homes to support elder and handicapped people. Specifically the system aims to design, build and validate an assistive ecosystem formed by a person living in a smart home with a social robot as her main interface to a gentler habitat. Achieving this goal requires the use and integration of different technologies and research areas, but also the development of the mechanisms in charge of providing an unified, pro-active response to the user's needs. This paper describes some of the mechanisms implemented within the cognitive robotics architecture CORTEX that integrates deliberative and reactive agents through a common understanding and internalizing of the outer reality, which materializes in a shared representation derived from a formal graph grammar.},\nauthor = {Bandera, A. and Bandera, J.P. and Bustos, P. and F{\\'{e}}rnandez, F. and Garc{\\'{i}}a-Olaya, A. and Garc{\\'{i}}a-Polo, J. and Garc{\\'{i}}a-Varea, I. and Manso, L.J. and Marfil, R. and Mart{\\'{i}}nez-G{\\'{o}}mez, J. and N{\\'{u}}{\\~{n}}ez, P. and Perez-Lorenzo, J.M. and Reche-Lopez, P. and Romero-Gonz{\\'{a}}lez, C. and Viciana-Abad, R.},\nbooktitle = {Advances in Intelligent Systems and Computing},\ndoi = {10.1007/978-3-319-70833-1_32},\nissn = {21945357},\nkeywords = {Assistive robotics,Lifelong technologies,Smart homes,Social robots,Software architectures},\ntitle = {{LifeBots I: Building the software infrastructure for supporting lifelong technologies}},\nvolume = {693},\nyear = {2018}\n}\n

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\n \n\n \n \n \n \n \n Enhancing a robotic rehabilitation model for hand-arm bimanual intensive therapy.\n \n \n \n\n\n \n Estévez, E.; Portales, I.; Pulido, J.; Fuentetaja, R.; and Fernández, F.\n\n\n \n\n\n\n Volume 693 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@book{Estevez2018,\nabstract = {{\\textcopyright} Springer International Publishing AG 2018. NAOTherapist is a robotic framework that aims at developing socially-interactive rehabilitation sessions for pediatric patients with physical impairments. Although this therapeutic tool has been already assessed with the target patients in a long-term evaluation, the system is planned to participate in an Hand-Arm Bimanual Therapy Camp for Cerebral Palsy patients. This presents new challenges and requirements that must be considered to provide a better daily experience to the involved participants. This work describes how the robotic rehabilitation model used in the previous version of the platform has been improved for both the inclusion of new games and the individual adaptation.},\nauthor = {Est{\\'{e}}vez, E.G. and Portales, I.D. and Pulido, J.C. and Fuentetaja, R. and Fern{\\'{a}}ndez, F.},\nbooktitle = {Advances in Intelligent Systems and Computing},\ndoi = {10.1007/978-3-319-70833-1_31},\nissn = {21945357},\nkeywords = {Hand-arm bimanual intensive therapies,NAOTherapist,Robotic rehabilitation model,Socially assistive robotics},\ntitle = {{Enhancing a robotic rehabilitation model for hand-arm bimanual intensive therapy}},\nvolume = {693},\nyear = {2018}\n}\n

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\n \n\n \n \n \n \n \n \n LifeBots I: Building the Software Infrastructure for Supporting Lifelong Technologies.\n \n \n \n \n\n\n \n Bandera, A.; Bandera, J. P; Bustos, P.; Férnandez, F.; García-Olaya, A.; García-Polo, J.; García-Varea, I.; Manso, L. J; Marfil, R.; Martínez-Gómez, J.; Núñez, P.; Perez-Lorenzo, J. M; Reche-Lopez, P.; Romero-González, C.; and Viciana-Abad, R.\n\n\n \n\n\n\n In Ollero, A.; Sanfeliu, A.; Montano, L.; Lau, N.; and Cardeira, C., editor(s), Advances in Intelligent Systems and Computing, pages 391–402, Cham, 2018. Springer International Publishing\n \n\n\n\n
\n\n\n\n \n \n $\"LifeBots$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Bandera2018,\nabstract = {The goal of the LifeBots project is the study and development of long-life mechanisms that facilitate and improve the integration of robotics platforms in smart homes to support elder and handicapped people. Specifically the system aims to design, build and validate an assistive ecosystem formed by a person living in a smart home with a social robot as her main interface to a gentler habitat. Achieving this goal requires the use and integration of different technologies and research areas, but also the development of the mechanisms in charge of providing an unified, pro-active response to the user's needs. This paper describes some of the mechanisms implemented within the cognitive robotics architecture CORTEX that integrates deliberative and reactive agents through a common understanding and internalizing of the outer reality, which materializes in a shared representation derived from a formal graph grammar.},\naddress = {Cham},\nauthor = {Bandera, Antonio and Bandera, Juan P and Bustos, Pablo and F{\\'{e}}rnandez, Fernando and Garc{\\'{i}}a-Olaya, Angel and Garc{\\'{i}}a-Polo, Javier and Garc{\\'{i}}a-Varea, Ismael and Manso, Luis J and Marfil, Rebeca and Mart{\\'{i}}nez-G{\\'{o}}mez, Jes{\\'{u}}s and N{\\'{u}}{\\~{n}}ez, Pedro and Perez-Lorenzo, Jose M and Reche-Lopez, Pedro and Romero-Gonz{\\'{a}}lez, Cristina and Viciana-Abad, Raquel},\nbooktitle = {Advances in Intelligent Systems and Computing},\ndoi = {10.1007/978-3-319-70833-1_32},\neditor = {Ollero, Anibal and Sanfeliu, Alberto and Montano, Luis and Lau, Nuno and Cardeira, Carlos},\nisbn = {978-3-319-70833-1},\npages = {391--402},\npublisher = {Springer International Publishing},\ntitle = {{LifeBots I: Building the Software Infrastructure for Supporting Lifelong Technologies}},\nurl = {http://link.springer.com/10.1007/978-3-319-70833-1{\\_}32},\nyear = {2018}\n}\n

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\n \n\n \n \n \n \n \n \n CLARC: A Cognitive Robot for Helping Geriatric Doctors in Real Scenarios.\n \n \n \n \n\n\n \n Voilmy, D.; Suárez, C.; Romero-Garcés, A.; Reuther, C.; Pulido, J. C.; Marfil, R.; Manso, L. J; Lan Hing Ting, K.; Iglesias, A.; González, J. C.; García, J.; García-Olaya, A.; Fuentetaja, R.; Fernández, F.; Dueñas, A.; Calderita, L. V.; Bustos, P.; Barile, T; Bandera, J. P.; and Bandera, A.\n\n\n \n\n\n\n In Ollero, A.; Sanfeliu, A.; Montano, L.; Lau, N.; and Cardeira, C., editor(s), Advances in Intelligent Systems and Computing, pages 403–414, Cham, 2018. Springer International Publishing\n \n\n\n\n
\n\n\n\n \n \n $\"CLARC:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Voilmy2018,\nabstract = {Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate the frailty of elderly persons in order to create therapy plans that improve their quality of life. For robotizing these tests, we are designing and developing CLARC, a mobile robot able to help the physician to capture and manage data during the CGA procedures, mainly by autonomously conducting a set of predefined evaluation tests. Built around a shared internal representation of the outer world, the architecture is composed of software modules able to plan and generate a stream of actions, to execute actions emanated from the representation or to update this by including/removing items at different abstraction levels. Percepts, actions and intentions coming from all software modules are grounded within this unique representation. This allows the robot to react to unexpected events and to modify the course of action according to the dynamics of a scenario built around the interaction with the patient. The paper describes the architecture of the system as well as the preliminary user studies and evaluation to gather new user requirements.},\naddress = {Cham},\nauthor = {Voilmy, Dimitri and Su{\\'{a}}rez, Cristina and Romero-Garc{\\'{e}}s, Adrian and Reuther, Cristian and Pulido, Jos{\\'{e}} Carlos and Marfil, Rebeca and Manso, Luis J and {Lan Hing Ting}, Karine and Iglesias, Ana and Gonz{\\'{a}}lez, Jos{\\'{e}} Carlos and Garc{\\'{i}}a, Javier and Garc{\\'{i}}a-Olaya, Angel and Fuentetaja, Raquel and Fern{\\'{a}}ndez, Fernando and Due{\\~{n}}as, Alvaro and Calderita, Luis Vicente and Bustos, Pablo and Barile, T and Bandera, Juan Pedro and Bandera, Antonio},\nbooktitle = {Advances in Intelligent Systems and Computing},\ndoi = {10.1007/978-3-319-70833-1_33},\neditor = {Ollero, Anibal and Sanfeliu, Alberto and Montano, Luis and Lau, Nuno and Cardeira, Carlos},\nisbn = {978-3-319-70833-1},\npages = {403--414},\npublisher = {Springer International Publishing},\ntitle = {{CLARC: A Cognitive Robot for Helping Geriatric Doctors in Real Scenarios}},\nurl = {http://link.springer.com/10.1007/978-3-319-70833-1{\\_}33},\nyear = {2018}\n}\n

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\n \n\n \n \n \n \n \n \n MDPbiome: microbiome engineering through prescriptive perturbations.\n \n \n \n \n\n\n \n García-Jiménez, B.; De la Rosa, T.; and Wilkinson, M. D\n\n\n \n\n\n\n Bioinformatics, 34(17): i838-i847. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"MDPbiome:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{MDPbiome2018, \n    author = {Garc{\\'{i}}a-Jim{\\'{e}}nez, Beatriz and {De la Rosa}, Tom{\\'{a}}s and Wilkinson, Mark D}, \n    title = {MDPbiome: microbiome engineering through prescriptive perturbations}, \n    journal = {Bioinformatics}, \n    volume = {34}, \n    number = {17}, \n    pages = {i838-i847}, \n    year = {2018}, \n    doi = {10.1093/bioinformatics/bty562}, \n    URL = {http://dx.doi.org/10.1093/bioinformatics/bty562}, \n    eprint = {/oup/backfile/content_public/journal/bioinformatics/34/17/10.1093_bioinformatics_bty562/2/bty562.pdf} \n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Counterplanning in Real-Time Strategy Games through Goal Recognition.\n \n \n \n \n\n\n \n Pozanco, A.; Blanco, A.; E-Martín, Y.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of Workshop on Goal Reasoning at IJCAI'18, Stockholm (Sweden), 2018. \n \n\n\n\n
\n\n\n\n \n \n $\"Counterplanning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{workshop-ijcai18,\n\n  author = {Alberto Pozanco and Alejandro Blanco and Yolanda E-Martín and Susana Fernández and Daniel Borrajo},\n\n  title = {Counterplanning in Real-Time Strategy Games through Goal Recognition},\n\n  booktitle = {Proceedings of Workshop on Goal Reasoning at IJCAI'18},\n\n  optcrossref = {},\n\n  key = {Planning-Learning},\n\n  cicyt = {workshops},\n\n  jcr = {},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  year = {2018},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {Stockholm (Sweden)},\n\n  optmonth = {},\n\n  optpages = {},\n\n  note = {},\n\n  url = {workshop-ijcai18.pdf},\n\n  optannote = {https://dtdannen.github.io/faim2018grw/papers/CounterplanninginReal-TimeStrategyGamesthroughGoalRecognition.pdf}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Efficient Approaches for Multi-Agent Planning.\n \n \n \n \n\n\n \n Borrajo, D.; and Fernández, S.\n\n\n \n\n\n\n Knowledge and Information Systems,1–55. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Efficient$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{kais-mapr,\n\n  author = {Daniel Borrajo and Susana Fernández},\n\n  title = {Efficient Approaches for Multi-Agent Planning},\n\n  journal = {Knowledge and Information Systems},\n\n  year = {2018},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  jcr = {Q2, 2016: 2.004 (57/133), Computer Science. Information Systems (67/146)},\n\n  publisher = {Springer Nature},\n\n  url = {https://doi.org/10.1007/s10115-018-1202-1},\n\n  optkey = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  month = {May},\n\n  pages = {1--55},\n\n  optisbn = {Printed 0219-1377, On-line 5-018-1202-1},\n\n  note = {},\n\n  optannote = {15-12-2015. 20-12-2016.}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Symbolic Perimeter Abstraction Heuristics for Cost-Optimal Planning.\n \n \n \n \n\n\n \n Torralba, Á.; Linares-López, C.; and Borrajo, D.\n\n\n \n\n\n\n Artificial Intelligence, 259: 1–31. June 2018.\n https://doi.org/10.1016/j.artint.2018.02.002\n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{spa-aij,\n\n  author = {Álvaro Torralba and Carlos Linares-López and Daniel Borrajo},\n\n  title = {Symbolic Perimeter Abstraction Heuristics for Cost-Optimal Planning},\n\n  journal = {Artificial Intelligence},\n\n  year = {2018},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  jcr = {Q1, 2016: 4.797 (14/133)},\n\n  publisher = {Elsevier},\n\n  optkey = {},\n\n  volume = {259},\n\n  optnumber = {},\n\n  month = {June},\n\n  pages = {1--31},\n\n  url = {aij18.pdf},\n\n  note = {https://doi.org/10.1016/j.artint.2018.02.002},\n\n  optannote = {24-12-2015}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Heterogeneus Multi-agent Planning Using Actuation Maps.\n \n \n \n \n\n\n \n Pereira, T.; Luis, N.; Fernández, S.; Borrajo, D.; Moreira, A. P.; and Veloso, M.\n\n\n \n\n\n\n In Proceedings of IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), pages 219–224, 2018. \n \n\n\n\n
\n\n\n\n \n \n $\"Heterogeneus$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icarsc,\n\n  author = {Tiago Pereira and Nerea Luis and Susana Fernández and Daniel Borrajo\n\n                  and António Paulo Moreira and Manuela Veloso},\n\n  title = {Heterogeneus Multi-agent Planning Using Actuation Maps},\n\n  booktitle = {Proceedings of IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  opturl = {},\n\n  year = {2018},\n\n  cicyt = {congresos},\n\n  key = {Planning-Learning},\n\n  jcr = {},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {},\n\n  optmonth = {},\n\n  pages = {219--224},\n\n  url = {https://ieeexplore.ieee.org/document/8374186/},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Counterplanning using Goal Recognition and Landmarks.\n \n \n \n \n\n\n \n Pozanco, A.; Escudero, Y.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of IJCAI'18, pages 4808–4814, Stockholm (Sweden), 2018. \n \n\n\n\n
\n\n\n\n \n \n $\"Counterplanning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ijcai18-counterplanning,\n\n  author = {Alberto Pozanco and Yolanda Escudero and Susana Fernández and Daniel Borrajo},\n\n  title = {Counterplanning using Goal Recognition and Landmarks},\n\n  booktitle = {Proceedings of IJCAI'18},\n\n  optcrossref = {},\n\n  key = {Planning-Learning},\n\n  cicyt = {congresos-buenos},\n\n  jcr = {A*},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  year = {2018},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {Stockholm (Sweden)},\n\n  optmonth = {},\n\n  pages = {4808--4814},\n\n  url = {http://www.ijcai.org/proceedings/2018/0668.pdf},\n\n  note = {},\n\n  optannote = {20.5\\% acceptance rate}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Distributed Planning and Model Learning for Urban Traffic Control.\n \n \n \n \n\n\n \n Pozanco, A.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of Workshop on Knowledge Engineering for Planning and Scheduling, ICAPS'18, Delft (Holanda), 2018. \n \n\n\n\n
\n\n\n\n \n \n $\"Distributed$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{keps18-traffic,\n\n  author = {Alberto Pozanco and Susana Fernández and Daniel Borrajo},\n\n  title = {Distributed Planning and Model Learning for Urban Traffic Control},\n\n  booktitle = {Proceedings of Workshop on Knowledge Engineering for Planning and Scheduling, ICAPS'18},\n\n  optcrossref = {},\n\n  key = {Planning-Learning},\n\n  cicyt = {workshops},\n\n  jcr = {},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  year = {2018},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {Delft (Holanda)},\n\n  optmonth = {},\n\n  optpages = {},\n\n  url = {keps18-traffic.pdf},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Meta-Search Through the Space of Representations and Heuristics on a Problem by Problem Basis.\n \n \n \n \n\n\n \n Fuentetaja, R.; Barley, M. W.; Borrajo, D.; Douglas, J.; Franco, S.; and Riddle, P.\n\n\n \n\n\n\n In Proceedings of AAAI'18, New Orleans (EEUU), 2018. \n \n\n\n\n
\n\n\n\n \n \n $\"Meta-Search$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 5 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{aaai18-msp,\n\n  author = {Raquel Fuentetaja and Michael W. Barley and Daniel Borrajo and Jordan Douglas and Santiago Franco and\n\n                  Patricia Riddle},\n\n  title = {Meta-Search Through the Space of Representations and Heuristics on a Problem by Problem Basis},\n\n  booktitle = {Proceedings of AAAI'18},\n\n  optcrossref = {},\n\n  key = {Planning-Learning},\n\n  cicyt = {congresos-buenos},\n\n  jcr = {A*},\n\n  url = {aaai18},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  year = {2018},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {New Orleans (EEUU)},\n\n  optmonth = {},\n\n  optpages = {},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Anticipation of Goals in Automated Planning.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; and de la Rosa, T.\n\n\n \n\n\n\n AI Communications, 31(2): 117–135. 2018.\n https://content.iospress.com/articles/ai-communications/aic753, DOI 10.3233/AIC-180753\n\n\n\n
\n\n\n\n \n \n $\"Anticipation$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 12 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aicomm18-anticipatory,\n\n  author = {Raquel Fuentetaja and Daniel Borrajo and Tomás de la Rosa},\n\n  title = {Anticipation of Goals in Automated Planning},\n\n  journal = {AI Communications},\n\n  year = {2018},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  jcr = {Q4, 2016: 0.654 (116/133)},\n\n  publisher = {IOS Press},\n\n  issn = {ISSN on-line: 1875-8452},\n\n  volume = {31},\n\n  number = {2},\n\n  optmonth = {},\n\n  url = {aicomm18-anticipatory.pdf},\n\n  pages = {117--135},\n\n  note = {https://content.iospress.com/articles/ai-communications/aic753, DOI 10.3233/AIC-180753},\n\n  optannote = {14-12-2016. Special Issue on Goal Reasoning. replied 31-Feb-2017}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Learning-driven Goal Generation.\n \n \n \n \n\n\n \n Pozanco, A.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n AI Communications, 31(2): 137–150. 2018.\n https://content.iospress.com/articles/ai-communications/aic754, DOI: 10.3233/AIC-180754\n\n\n\n
\n\n\n\n \n \n $\"Learning-driven$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aicomm18-learning,\n\n  author = {Alberto Pozanco and Susana Fernández and Daniel Borrajo},\n\n  title = {Learning-driven Goal Generation},\n\n  journal = {AI Communications},\n\n  year = {2018},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  jcr = {Q4, 2016: 0.654 (116/133)},\n\n  publisher = {IOS Press},\n\n  issn = {ISSN on-line: 1875-8452},\n\n  volume = {31},\n\n  number = {2},\n\n  optmonth = {},\n\n  url = {aicomm18-learning.pdf},\n\n  pages = {137--150},\n\n  note = {https://content.iospress.com/articles/ai-communications/aic754, DOI: 10.3233/AIC-180754},\n\n  optannote = {14-12-2016. Special Issue on Goal Reasoning}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Special issue on goal reasoning.\n \n \n \n\n\n \n Roberts, M.; Borrajo, D.; Cox, M.; and Yorke-Smith, N.\n\n\n \n\n\n\n AI Communications, 31(2): 115–116. 2018.\n DOI: 10.3233/AIC-180754\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@Article{aicomm18-editorial,\n  author =      {Mark Roberts and Daniel Borrajo and Michael Cox and Neil Yorke-Smith},\n  title =      {Special issue on goal reasoning},\n  journal =      {AI Communications},\n  year =      {2018},\n  key =          {No Planning-Learning},\n  cicyt =        {editor},\n  jcr =          {Q4, 2017: 0.461 (127/132)},\n  publisher =    {IOS Press},\n  issn =         {ISSN on-line: 1875-8452},\n  OPTkey =      {},\n  volume =     {31},\n  number =     {2},\n  OPTmonth =      {},\n  pages =     {115--116},\n  note =     {DOI: 10.3233/AIC-180754},\n  OPTannote =      {14-12-2016. Special Issue on Goal Reasoning}\n}\n\n

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\n \n\n \n \n \n \n \n Modeling, evaluation, and scale on artificial pedestrians: A literature review.\n \n \n \n\n\n \n Martinez-Gil, F.; Lozano, M.; García-Fernández, I.; and Fernández, F.\n\n\n \n\n\n\n ACM Computing Surveys, 50(5). 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Martinez-Gil2017a,\nabstract = {{\\textcopyright} 2017 ACM. Modeling pedestrian dynamics and their implementation in a computer are challenging and important issues in the knowledge areas of transportation and computer simulation. The aim of this article is to provide a bibliographic outlook so that the reader may have quick access to the most relevant works related to this problem. We have used three main axes to organize the article's contents: pedestrian models, validation techniques, and multiscale approaches. The backbone of this work is the classification of existing pedestrian models; we have organized the works in the literature under five categories, according to the techniques used for implementing the operational level in each pedestrian model. Then the main existing validation methods, oriented to evaluate the behavioral quality of the simulation systems, are reviewed. Furthermore, we review the key issues that arise when facing multiscale pedestrian modeling, where we first focus on the behavioral scale (combinations of micro and macro pedestrian models) and second on the scale size (from individuals to crowds). The article begins by introducing the main characteristics of walking dynamics and its analysis tools and concludes with a discussion about the contributions that different knowledge fields can make in the near future to this exciting area.},\nauthor = {Martinez-Gil, F. and Lozano, M. and Garc{\\'{i}}a-Fern{\\'{a}}ndez, I. and Fern{\\'{a}}ndez, F.},\ndoi = {10.1145/3117808},\nissn = {15577341},\njournal = {ACM Computing Surveys},\nkeywords = {Crowds,Macroscopic and microscopic pedestrian models,Multiscale simulation,Pedestrian modeling and simulation,Validation methods},\nnumber = {5},\ntitle = {{Modeling, evaluation, and scale on artificial pedestrians: A literature review}},\nvolume = {50},\nyear = {2017}\n}\n

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\n \n\n \n \n \n \n \n Performance modelling of planners from homogeneous problem sets.\n \n \n \n\n\n \n De La Rosa, T.; Cenamor, I.; and Fernández, F.\n\n\n \n\n\n\n In Proceedings International Conference on Automated Planning and Scheduling, ICAPS, 2017. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{DeLaRosa2017,\nabstract = {Copyright {\\textcopyright} 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). Empirical performance models play an important role in the development of planning portfolios that make a per-domain or per-problem configuration of its search components. Even though such portfolios have shown their power when compared to other systems in current benchmarks, there is no clear evidence that they are capable to differentiate problems (instances) having similar input properties (in terms of objects, goals, etc.) but fairly different runtime for a given planner. In this paper we present a study of empirical performance models that are trained using problems having the same configuration, with the objective of guiding the models to recognize the underlying differences existing among homogeneous problems. In addition we propose a set of new features that boost the prediction capabilities under such scenarios. The results show that the learned models clearly performed over random classifiers, which reinforces the hypothesis that the selection of planners can be done on a per-instance basis when configuring a portfolio.},\nauthor = {{De La Rosa}, T. and Cenamor, I. and Fern{\\'{a}}ndez, F.},\nbooktitle = {Proceedings International Conference on Automated Planning and Scheduling, ICAPS},\nisbn = {9781577357896},\nissn = {23340843},\ntitle = {{Performance modelling of planners from homogeneous problem sets}},\nyear = {2017}\n}\n

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\n \n\n \n \n \n \n \n \n Evaluating the Child–Robot Interaction of the NAOTherapist Platform in Pediatric Rehabilitation.\n \n \n \n \n\n\n \n Pulido, J. C.; González, J. C.; Suárez-Mejías, C.; Bandera, A.; Bustos, P.; and Fernández, F.\n\n\n \n\n\n\n International Journal of Social Robotics, 9(3): 343–358. jun 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Evaluating$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Pulido2017,\nabstract = {NAOTherapist is a cognitive robotic archi- tecture whose main goal is to develop non-contact upper- limb rehabilitation sessions autonomously with a social robot for patients with physical impairments. In order to achieve a fluent interaction and an active engagement with the patients, the system should be able to adapt by itself in accordance with the perceived environment. In this paper, we describe the interaction mechanisms that are necessary to supervise and help the patient to carry out the prescribed exercises correctly. We also provide an evaluation focused on the child-robot interaction of the robotic platform with a large number of schoolchil- dren and the experience of a first contact with three pediatric rehabilitation patients. The results presented are obtained through questionnaires, video analysis and system logs, and have proven to be consistent with the hypotheses proposed in this work.},\nauthor = {Pulido, Jos{\\'{e}} Carlos and Gonz{\\'{a}}lez, Jos{\\'{e}} Carlos and Su{\\'{a}}rez-Mej{\\'{i}}as, Cristina and Bandera, Antonio and Bustos, Pablo and Fern{\\'{a}}ndez, Fernando},\ndoi = {10.1007/s12369-017-0402-2},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2Fs12369-017-0402-2.pdf:pdf},\nissn = {1875-4791},\njournal = {International Journal of Social Robotics},\nkeywords = {Automated Planning,Control Architectures and Programming,Rehabilitation Robotics,Social Human-Robot Interaction,Socially Assistive Robotics},\nmonth = {jun},\nnumber = {3},\npages = {343--358},\npublisher = {Springer Netherlands},\ntitle = {{Evaluating the Child–Robot Interaction of the NAOTherapist Platform in Pediatric Rehabilitation}},\nurl = {http://link.springer.com/10.1007/s12369-017-0402-2},\nvolume = {9},\nyear = {2017}\n}\n

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\n \n\n \n \n \n \n \n \n A three-layer planning architecture for the autonomous control of rehabilitation therapies based on social robots.\n \n \n \n \n\n\n \n González, J. C.; Pulido, J. C.; and Fernández, F.\n\n\n \n\n\n\n Cognitive Systems Research, 43: 232–249. jun 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Gonzalez2017,\nabstract = {{\\textcopyright} 2016 Elsevier B.V.This manuscript focuses on the description of a novel cognitive architecture called NAOTherapist, which provides a social robot with enough autonomy to carry out a non-contact upper limb rehabilitation therapy for patients with physical impairments, such as cerebral palsy and obstetric brachial plexus palsy. NAOTherapist comprises three levels of Automated Planning. In the high-level planning, the physician establishes the parameters of the therapy such as the scheduling of the sessions, the therapeutic objectives to be achieved and certain constraints based on the medical records of the patient. This information is used to establish a customized therapy plan. The objective of the medium-level planning is to execute and monitor every previous planned session with the humanoid robot. Finally, the low-level planning involves the execution of path-planning actions by the robot to carry out different low-level instructions such as performing poses. The technical evaluation shows an accurate definition and monitoring of the therapies and sessions and a fluent interaction with the robot. This automated process is expected to save time for the professionals while guaranteeing the medical criteria.},\nauthor = {Gonz{\\'{a}}lez, Jos{\\'{e}} Carlos and Pulido, Jos{\\'{e}} Carlos and Fern{\\'{a}}ndez, Fernando},\ndoi = {10.1016/j.cogsys.2016.09.003},\nfile = {:home/fernando/papers/tmp/1-s2.0-S138904171630064X-main.pdf:pdf},\nisbn = {1389-0417},\nissn = {13890417},\njournal = {Cognitive Systems Research},\nkeywords = {Automated Planning,Human-Robot Interaction,Rehabilitation therapies,Robotic architecture,Socially Assistive Robotics},\nmonth = {jun},\npages = {232--249},\ntitle = {{A three-layer planning architecture for the autonomous control of rehabilitation therapies based on social robots}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S138904171630064X},\nvolume = {43},\nyear = {2017}\n}\n

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\n \n\n \n \n \n \n \n \n Emergent behaviors and scalability for multi-agent reinforcement learning-based pedestrian models.\n \n \n \n \n\n\n \n Martinez-Gil, F.; Lozano, M.; and Fernández, F.\n\n\n \n\n\n\n Simulation Modelling Practice and Theory, 74: 117–133. may 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Emergent$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Martinez-Gil2017,\nabstract = {{\\textcopyright} 2017This paper analyzes the emergent behaviors of pedestrian groups that learn through the multiagent reinforcement learning model developed in our group. Five scenarios studied in the pedestrian model literature, and with different levels of complexity, were simulated in order to analyze the robustness and the scalability of the model. Firstly, a reduced group of agents must learn by interaction with the environment in each scenario. In this phase, each agent learns its own kinematic controller, that will drive it at a simulation time. Secondly, the number of simulated agents is increased, in each scenario where agents have previously learnt, to test the appearance of emergent macroscopic behaviors without additional learning. This strategy allows us to evaluate the robustness and the consistency and quality of the learned behaviors. For this purpose several tools from pedestrian dynamics, such as fundamental diagrams and density maps, are used. The results reveal that the developed model is capable of simulating human-like micro and macro pedestrian behaviors for the simulation scenarios studied, including those where the number of pedestrians has been scaled by one order of magnitude with respect to the situation learned.},\nauthor = {Martinez-Gil, Francisco and Lozano, Miguel and Fern{\\'{a}}ndez, Fernando},\ndoi = {10.1016/j.simpat.2017.03.003},\nfile = {:home/fernando/papers/tmp/1-s2.0-S1569190X17300503-main.pdf:pdf},\nissn = {1569190X},\njournal = {Simulation Modelling Practice and Theory},\nkeywords = {Behavioural simulation,Emergent behaviours,Multi-Agent Reinforcement Learning (MARL),Pedestrian simulation and modeling},\nmonth = {may},\npages = {117--133},\ntitle = {{Emergent behaviors and scalability for multi-agent reinforcement learning-based pedestrian models}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S1569190X17300503},\nvolume = {74},\nyear = {2017}\n}\n

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\n \n\n \n \n \n \n \n GOTCHA: An Autonomous Controller for the Space Domain.\n \n \n \n\n\n \n Ocon, J.; Delfa, J. M.; de la Rosa, T.; Garcia-Olaya, A.; and Escudero, Y.\n\n\n \n\n\n\n In Proceedings of the Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA), Leiden, 2017. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ocon2017,\naddress = {Leiden},\nauthor = {Ocon, Jorge and Delfa, Juan Manuel and de la Rosa, Tom{\\'{a}}s and Garcia-Olaya, Angel and Escudero, Yolanda},\nbooktitle = {Proceedings of the Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA)},\nmendeley-groups = {Papers/2018-IJCAI-Gotcha},\ntitle = {{GOTCHA: An Autonomous Controller for the Space Domain}},\nyear = {2017}\n}\n

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\n \n\n \n \n \n \n \n On the Application of Classical Planning to Real Social Robotic Tasks.\n \n \n \n\n\n \n González, J. C.; Fernández, F.; García-Olaya, A.; and Fuentetaja, R.\n\n\n \n\n\n\n In Finzi, A.; Karpas, E.; and Nejat, G., editor(s), Proceedings of the 5th Workshop on Planning and Robotics. International Conference on Automated Planning and Scheduling, pages 38–47, 2017. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Gonzalez2017,\nauthor = {Gonz{\\'{a}}lez, Jos{\\'{e}} Carlos and Fern{\\'{a}}ndez, Fernando and Garc{\\'{i}}a-Olaya, Angel and Fuentetaja, Raquel},\nbooktitle = {Proceedings of the 5th Workshop on Planning and Robotics. International Conference on Automated Planning and Scheduling},\neditor = {Finzi, Alberto and Karpas, Erez and Nejat, Goldie},\nfile = {:C$\\backslash$:/Users/angel/Documents/Mendeley Desktop/Gonz{\\'{a}}lez et al. - 2017 - On the Application of Classical Planning to Real Social Robotic Tasks.pdf:pdf},\npages = {38--47},\ntitle = {{On the Application of Classical Planning to Real Social Robotic Tasks}},\nyear = {2017}\n}\n

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\n \n\n \n \n \n \n \n Incremental contingency planning for recovering from critical outcomes in high-probability seed plans.\n \n \n \n\n\n \n E-Martín, Y.; R-Moreno, M.; and Smith, D. E.\n\n\n \n\n\n\n Progress in Artificial Intelligence, 6(4): 299–314. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{yolanda2017incremental,\n  title={Incremental contingency planning for recovering from critical outcomes in high-probability seed plans},\n  author={E-Mart\\'in, Yolanda and R-Moreno, Mar{\\'\\i}a D. and Smith, David E.},\n  journal={Progress in Artificial Intelligence},\n  volume={6},\n  number={4},\n  pages={299--314},\n  year={2017},\n  publisher={Springer}\n}\n\n\n

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\n \n\n \n \n \n \n \n \n Planning for Tourism Routes using Social Networks.\n \n \n \n \n\n\n \n Cenamor, I.; Núñez, S.; de la Rosa, T.; and Borrajo, D.\n\n\n \n\n\n\n Expert Systems with Applications, 69: 1–9. 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Planning$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{eswa-ondroad,\n\n  author = {Isabel Cenamor and Sergio Núñez and Tomás de la Rosa and Daniel Borrajo},\n\n  title = {Planning for Tourism Routes using Social Networks},\n\n  journal = {Expert Systems with Applications},\n\n  year = {2017},\n\n  publisher = {Elsevier},\n\n  key = {Planning-Learning},\n\n  url = {http://dx.doi.org/10.1016/j.eswa.2016.10.030},\n\n  volume = {69},\n\n  number = {},\n\n  issn = {0957-4174},\n\n  doi = {http://dx.doi.org/10.1016/j.eswa.2016.10.030},\n\n  month = {},\n\n  pages = {1--9},\n\n  cicyt = {revista},\n\n  jcr = {Q1, 2016: 3.928 (19/133)\\\\ En Engineering, electrical \\& electronic (37/262), En Operations research \\&\n\n                  Management science (3/83)},\n\n  optjcr = {2004: 1.247 (26/78), 2005: 1.236 (32/79), 2006: 0.957 (41/85), 2007: 1.177 (40/93), 2008: 2.596 (17/94)\\\\ En Categoría Operations Research \\& Management Science: 2007 (11/60), 2008 (1/64)},\n\n  note = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Planning for Tourism Routes using Social Networks.\n \n \n \n \n\n\n \n Cenamor, I.; Núñez, S.; de la Rosa, T.; and Borrajo, D.\n\n\n \n\n\n\n Expert Systems with Applications, 69: 1–9. 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Planning$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@Article{eswa-ondroad,\n  author =      {Isabel Cenamor and Sergio Núñez and Tomás de la Rosa and Daniel Borrajo},\n  title =      {Planning for Tourism Routes using Social Networks},\n  journal =      {Expert Systems with Applications},\n  year =      {2017},\n  publisher =    {Elsevier},\n  key =         {Planning-Learning},\n  url = {http://dx.doi.org/10.1016/j.eswa.2016.10.030},\n  volume =     {69},\n  number =     {},\n  issn = "0957-4174",\n  doi = "http://dx.doi.org/10.1016/j.eswa.2016.10.030",\n  month =     {},\n  pages =     {1--9},\n  cicyt =        {revista},\n  jcr =        {Q1, 2017: 3.768 (20/132)\\\\ En Engineering, electrical \\& electronic (42/260), En Operations research \\&\n                  Management science (8/84)},\n  OPTjcr =          {2004: 1.247 (26/78), 2005: 1.236 (32/79), 2006: 0.957 (41/85), 2007: 1.177 (40/93), 2008: 2.596 (17/94)\\\\ En Categoría Operations Research \\& Management Science: 2007 (11/60), 2008 (1/64)},\n  note =     {}\n}\n\n

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\n \n\n \n \n \n \n \n NAOTherapist: Autonomous Assistance of Physical Rehabilitation Therapies with a Social Humanoid Robot.\n \n \n \n\n\n \n Pulido, J. C.; González, J. C.; and Fernández, F.\n\n\n \n\n\n\n In International Workshop on Assistive & Rehabilitation Technology (IWART 2016), 2016. \n \n\n\n\n
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@inproceedings{Pulido2016,\nauthor = {Pulido, Jos{\\'{e}} Carlos and Gonz{\\'{a}}lez, Jos{\\'{e}} Carlos and Fern{\\'{a}}ndez, Fernando},\nbooktitle = {International Workshop on Assistive {\\&} Rehabilitation Technology (IWART 2016)},\nfile = {:home/fernando/papers/tmp/IWART2016{\\_}NAOTherapist.pdf:pdf},\ntitle = {{NAOTherapist: Autonomous Assistance of Physical Rehabilitation Therapies with a Social Humanoid Robot}},\nyear = {2016}\n}\n

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\n \n\n \n \n \n \n \n \n The IBaCoP planning system: Instance-based configured portfolios.\n \n \n \n \n\n\n \n Cenamor, I.; De La Rosa, T.; and Fernández, F.\n\n\n \n\n\n\n Journal of Artificial Intelligence Research, 56: 657–691. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Cenamor2016,\nabstract = {{\\textcopyright} 2016 AI Access Foundation. All rights reserved.Sequential planning portfolios are very powerful in exploiting the complementary strength of different automated planners. The main challenge of a portfolio planner is to define which base planners to run, to assign the running time for each planner and to decide in what order they should be carried out to optimize a planning metric. Portfolio configurations are usually derived empirically from training benchmarks and remain fixed for an evaluation phase. In this work, we create a per-instance configurable portfolio, which is able to adapt itself to every planning task. The proposed system pre-selects a group of candidate planners using a Pareto-dominance filtering approach and then it decides which planners to include and the time assigned according to predictive models. These models estimate whether a base planner will be able to solve the given problem and, if so, how long it will take. We define different portfolio strategies to combine the knowledge generated by the models. The experimental evaluation shows that the resulting portfolios provide an improvement when compared with non-informed strategies. One of the proposed portfolios was the winner of the Sequential Satisficing Track of the International Planning Competition held in 2014.},\nauthor = {Cenamor, I. and {De La Rosa}, T. and Fern{\\'{a}}ndez, F.},\ndoi = {10.1613/jair.5080},\nfile = {:home/fernando/papers/tmp/live-5080-9497-jair.pdf:pdf},\nissn = {10769757},\njournal = {Journal of Artificial Intelligence Research},\npages = {657--691},\ntitle = {{The IBaCoP planning system: Instance-based configured portfolios}},\nurl = {http://www.jair.org/papers/paper5080.html},\nvolume = {56},\nyear = {2016}\n}\n

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\n \n\n \n \n \n \n \n \n Planning and execution through variable resolution planning.\n \n \n \n \n\n\n \n Martínez, M.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n Robotics and Autonomous Systems, 83: 214–230. sep 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Planning$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Martinez2016,\nabstract = {{\\textcopyright} 2016 Elsevier B.V.Generating sequences of actions-plans-for robots using Automated Planning in stochastic and dynamic environments has been shown to be a difficult task with high computational complexity. These plans are composed of actions whose execution might fail due to different reasons. In many cases, if the execution of an action fails, it prevents the execution of some (or all) of the remainder actions in the plan. Therefore, in most real-world scenarios computing a complete and sound (valid) plan at each (re-)planning step is not worth the computational resources and time required to generate the plan. This is specially true given the high probability of plan execution failure. Besides, in many real-world environments, plans must be generated fast, both at the start of the execution and after every execution failure. In this paper, we present Variable Resolution Planning which uses Automated Planning to quickly compute a reasonable (not necessarily sound) plan. Our approach computes an abstract representation-removing some information from the planning task-which is used once a search depth of k steps has been reached. Thus, our approach generates a plan where the first k actions are applicable if the domain is stationary and deterministic, while the rest of the plan might not be necessarily applicable. The advantages of this approach are that it: is faster than regular full-fledged planning (both in the probabilistic or deterministic settings); does not spend much time on the far future actions that probably will not be executed, since in most cases it will need to replan before executing the end of the plan; and takes into account some information of the far future, as an improvement over pure reactive systems. We present experimental results on different robotics domains that simulate tasks on stochastic environments.},\nauthor = {Mart{\\'{i}}nez, Mois{\\'{e}}s and Fern{\\'{a}}ndez, Fernando and Borrajo, Daniel},\ndoi = {10.1016/j.robot.2016.04.009},\nfile = {:home/fernando/papers/tmp/1-s2.0-S0921889016302172-main.pdf:pdf},\nissn = {09218890},\njournal = {Robotics and Autonomous Systems},\nkeywords = {Abstract representation,Cognitive robotics,Planning and execution,Task planning},\nmonth = {sep},\npages = {214--230},\ntitle = {{Planning and execution through variable resolution planning}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S0921889016302172},\nvolume = {83},\nyear = {2016}\n}\n

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\n \n\n \n \n \n \n \n Percepts symbols or Action symbols? Generalizing how all modules interact within a software architecture for cognitive robotics.\n \n \n \n\n\n \n Marfil, R.; Manso, L. J; Bandera, J. P.; Romero-Garcés, A.; Bandera, A.; Bustos, P.; Calderita, L. V.; González, J. C.; García-Olaya, A.; Fuentetaja, R.; and Fernández, F.\n\n\n \n\n\n\n In Workshop of Physical Agents 2016, pages 9–16, 2016. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Marfil2016,\nabstract = {Robots require a close coupling of perception and action. Cognitive robots go beyond this to require a further coupling with cognition. From the perspective of robotics, this coupling generally emphasizes a tightly integrated perceptuomo- tor system, which is then loosely connected to some limited form of cognitive system such as a planner. At the other end, from the perspective of automated planning, the emphasis is on a highly functional system that, taken to its extreme, calls perceptual and motor modules as independent functions. This paper proposes to join both perspectives through a unique representation where the responses of all modules on the software architecture (percepts or actions) are grounded using the same set of symbols. This allows to generalize the signal-to-symbol divide that separates classic perceptuomotor and automated planning systems, being the result a software architecture where all software modules interact using the same tokens.},\nauthor = {Marfil, Rebeca and Manso, Luis J and Bandera, Juan Pedro and Romero-Garc{\\'{e}}s, Adrian and Bandera, Antonio and Bustos, Pablo and Calderita, Luis Vicente and Gonz{\\'{a}}lez, Jos{\\'{e}} Carlos and Garc{\\'{i}}a-Olaya, Angel and Fuentetaja, Raquel and Fern{\\'{a}}ndez, Fernando},\nbooktitle = {Workshop of Physical Agents 2016},\nfile = {:C$\\backslash$:/Users/angel/Documents/Mendeley Desktop/Marfil et al. - 2016 - Percepts symbols or Action symbols Generalizing how all modules interact within a software architecture for cogni.pdf:pdf},\nnumber = {June},\npages = {9--16},\ntitle = {{Percepts symbols or Action symbols? Generalizing how all modules interact within a software architecture for cognitive robotics}},\nyear = {2016}\n}\n

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\n \n\n \n \n \n \n \n CLARC : a Robotic Architecture for Comprehensive Geriatric Assessment.\n \n \n \n\n\n \n Bandera, A.; Bandera, J. P.; Bustos, P.; Calderita, L. V; Dueñas, A.; Fernández, F.; Fuentetaja, R.; García-Olaya, A.; García, F. J.; González, J. C.; Iglesias, A.; Manso, L. J; Marfil, R.; Pulido, J. C.; Reuther, C.; Romero-Garcés, A.; and Suárez, C.\n\n\n \n\n\n\n In Workshop on Physical Agents, pages 1–8, 2016. \n \n\n\n\n
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@inproceedings{Bandera2016,\nauthor = {Bandera, Antonio and Bandera, Juan Pedro and Bustos, Pablo and Calderita, Luis V and Due{\\~{n}}as, Alvaro and Fern{\\'{a}}ndez, Fernando and Fuentetaja, Raquel and Garc{\\'{i}}a-Olaya, Angel and Garc{\\'{i}}a, Francisco Javier and Gonz{\\'{a}}lez, Jos{\\'{e}} Carlos and Iglesias, Ana and Manso, Luis J and Marfil, Rebeca and Pulido, Jos{\\'{e}} Carlos and Reuther, Christian and Romero-Garc{\\'{e}}s, Adrian and Su{\\'{a}}rez, Cristina},\nbooktitle = {Workshop on Physical Agents},\nfile = {:C$\\backslash$:/Users/angel/Documents/Mendeley Desktop/Bandera et al. - 2016 - CLARC a Robotic Architecture for Comprehensive Geriatric Assessment.pdf:pdf},\nisbn = {978-84-608-8176-6},\nnumber = {June},\npages = {1--8},\ntitle = {{CLARC : a Robotic Architecture for Comprehensive Geriatric Assessment}},\nyear = {2016}\n}\n

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\n \n\n \n \n \n \n \n \n Urban Traffic Control Assisted by AI Planning and Relational Learning.\n \n \n \n \n\n\n \n Pozanco, A.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of 9th International Workshop on Agents in Traffic and Transportation (at IJCAI'16), volume 1678, of CEUR Workshop Proceedings, 2016. \n \n\n\n\n
\n\n\n\n \n \n $\"Urban$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{workshop-att16,\n\n  author = {Alberto Pozanco and Susana Fernández and Daniel Borrajo},\n\n  title = {Urban Traffic Control Assisted by AI Planning and Relational Learning},\n\n  booktitle = {Proceedings of 9th International Workshop on Agents in Traffic and Transportation (at IJCAI'16)},\n\n  optcrossref = {},\n\n  opteditor = {Ana Lúcia C. Bazzan and Franziska Klügl and Sascha Ossowski and Giuseppe Vizzari},\n\n  volume = {1678},\n\n  optnumber = {},\n\n  series = {CEUR Workshop Proceedings},\n\n  url = {http://ceur-ws.org/Vol-1678/paper6.pdf},\n\n  year = {2016},\n\n  cicyt = {workshops},\n\n  key = {Planning-Learning},\n\n  jcr = {},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {},\n\n  optmonth = {},\n\n  pages = {},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Planning and Execution through Variable Resolution Planning.\n \n \n \n \n\n\n \n Martínez, M.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n Robotics and Autonomous Systems, 83: 214–230. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Planning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ras16,\n\n  author = {Moisés Martínez and Fernando Fernández and Daniel Borrajo},\n\n  title = {Planning and Execution through Variable Resolution Planning},\n\n  journal = {Robotics and Autonomous Systems},\n\n  year = {2016},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  publisher = {Elsevier},\n\n  url = {http://dx.doi.org/10.1016/j.robot.2016.04.009},\n\n  volume = {83},\n\n  optnumber = {},\n\n  optmonth = {September},\n\n  pages = {214--230},\n\n  note = {},\n\n  jcr = {Q2, 2016: 1.950 Categoría: Automation \\& Control Systems (28/60), Categoría: Computer Science, Artificial\n\n                  Intelligence (60/133), Categoría: Robotics (14/26)},\n\n  optannote = {http://www.sciencedirect.com/science/article/pii/S0921889016302172}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n On Learning Planning Goals for Traffic Control.\n \n \n \n \n\n\n \n Pozanco, A.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of 4th Workshop on Goal Reasoning (IJCAI'16), 2016. \n \n\n\n\n
\n\n\n\n \n \n $\"On$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{workshop-ijcai16-learning,\n\n  author = {Alberto Pozanco and Susana Fernández and Daniel Borrajo},\n\n  title = {On Learning Planning Goals for Traffic Control},\n\n  booktitle = {Proceedings of 4th Workshop on Goal Reasoning (IJCAI'16)},\n\n  optcrossref = {},\n\n  optkey = {},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  url = {workshop-ijcai16-learning.pdf},\n\n  year = {2016},\n\n  cicyt = {workshops},\n\n  key = {Planning-Learning},\n\n  jcr = {},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {},\n\n  optmonth = {},\n\n  pages = {},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Anticipatory Search as Partial Satisfaction Planning with State Dependent Costs.\n \n \n \n \n\n\n \n Borrajo, D.; Fuentetaja, R.; and de la Rosa, T.\n\n\n \n\n\n\n In Proceedings of 4th Workshop on Goal Reasoning (IJCAI'16), 2016. \n \n\n\n\n
\n\n\n\n \n \n $\"Anticipatory$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{workshop-ijcai16-anticipatory,\n\n  author = {Daniel Borrajo and Raquel Fuentetaja and Tomás de la Rosa},\n\n  title = {Anticipatory Search as Partial Satisfaction Planning with State Dependent Costs},\n\n  booktitle = {Proceedings of 4th Workshop on Goal Reasoning (IJCAI'16)},\n\n  optcrossref = {},\n\n  optkey = {},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  url = {workshop-ijcai16-anticipatory.pdf},\n\n  year = {2016},\n\n  cicyt = {workshops},\n\n  key = {Planning-Learning},\n\n  jcr = {},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {},\n\n  optmonth = {},\n\n  pages = {},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Abstraction Heuristics for Symbolic Bidirectional Search.\n \n \n \n \n\n\n \n Torralba, Á.; Linares-López, C.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of IJCAI'16, New York (EEUU), 2016. \n \n\n\n\n
\n\n\n\n \n \n $\"Abstraction$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ijcai16-symba,\n\n  author = {{\\'A}lvaro Torralba and Carlos Linares-López and Daniel Borrajo},\n\n  title = {Abstraction Heuristics for Symbolic Bidirectional Search},\n\n  booktitle = {Proceedings of IJCAI'16},\n\n  optcrossref = {},\n\n  optkey = {},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  url = {ijcai16-symba.pdf},\n\n  year = {2016},\n\n  cicyt = {congresos-buenos},\n\n  key = {Planning-Learning},\n\n  jcr = {A*},\n\n  optorganization = {},\n\n  publisher = {},\n\n  address = {New York (EEUU)},\n\n  optmonth = {},\n\n  pages = {},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n .\n \n \n \n \n\n\n \n García, J.; Torralba, Á.; Flórez, J. E.; Borrajo, D.; Linares-López, C.; and García-Olaya, Á.\n\n\n \n\n\n\n of Autonomic Systems. TIMIPLAN: A Tool for Transportation Tasks, pages 269–285. McCluskey, T. L.; Kotsialos, A.; Müller, J. P.; Klügl, F.; Rana, O.; and Schumann, R., editor(s). Birkhäuser/Springer, 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"TIMIPLAN:$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inbook{arts-book,\n\n  author = {Javier García and Álvaro Torralba and José E. Flórez and Daniel Borrajo and Carlos Linares-López and\n\n                  Ángel García-Olaya},\n\n  booktitle = {Autonomic Road Transport Support Systems},\n\n  title = {{TIMIPLAN: A Tool for Transportation Tasks}},\n\n  publisher = {Birkhäuser/Springer},\n\n  year = {2016},\n\n  key = {Planning-Learning},\n\n  editor = {Thomas Leo McCluskey and Apostolos Kotsialos and Jörg P. Müller and Franziska Klügl and Omer Rana and René Schumann},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  url = {http://link.springer.com/chapter/10.1007/978-3-319-25808-9_16},\n\n  series = {Autonomic Systems},\n\n  cicyt = {capitulos},\n\n  optaddress = {},\n\n  optedition = {},\n\n  optmonth = {},\n\n  pages = {269--285},\n\n  opttype = {},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using Automated Planning for Traffic Signals Control.\n \n \n \n \n\n\n \n Gulic̀, M.; Olivares, R.; and Borrajo, D.\n\n\n \n\n\n\n PROMET - Traffic&Transportation, 28(4): 383–391. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{promet15,\n\n  author = {Matija Guli\\`{c} and Ricardo Olivares and Daniel Borrajo},\n\n  title = {Using Automated Planning for Traffic Signals Control},\n\n  journal = {PROMET - Traffic\\&Transportation},\n\n  volume = {28},\n\n  number = {4},\n\n  year = {2016},\n\n  url = {},\n\n  publisher = {},\n\n  address = {},\n\n  key = {Planning-Learning},\n\n  month = {},\n\n  pages = {383--391},\n\n  cicyt = {revista-noJCR},\n\n  jcr = {SCI Expanded. Factor de impacto: 0.27 (2014). 30/33 en Categoría Transportation Science \\& Technology - SCIE},\n\n  note = {},\n\n  optannote = {2-Sept-2015. ISSN 0353/5320. It is on the SCI Expanded, not in the SCI}\n\n}\n\n\n\n

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\n \n 2015\n \n \n (13)\n \n \n

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\n \n\n \n \n \n \n \n \n Heuristics as Markov Chains.\n \n \n \n \n\n\n \n Linares López, C.\n\n\n \n\n\n\n Annals of Mathematics and Artificial Intelligence, 73(3-4): 275–309. April 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Heuristics$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@Article{\t  linares-lopez.c:heuristics,\n  author\t= {Carlos {Linares L\\'opez}},\n  title\t\t= {Heuristics as Markov Chains},\n  journal\t= {Annals of Mathematics and Artificial Intelligence},\n  year\t\t= {2015},\n  volume\t= {73},\n  number        = {3-4},\n  pages\t\t= {275--309},\n  month         = apr,\n  doi\t\t= {10.1007/s10472-014-9439-1},\n  url\t\t= {link.springer.com/article/10.1007/s10472-014-9439-1}\n}\n\n

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\n \n\n \n \n \n \n \n \n Gualzru's path to the advertisement world.\n \n \n \n \n\n\n \n Fernández, F.; Martínez, M.; García-Varea, I.; Martínez-Gómez, J.; Pérez-Lorenzo, J.; Viciana, R.; Bustos, P.; Manso, L.; Calderita, L.; Gutiérrez, M.; Núñez, P.; Bandera, A.; Romero-Garcés, A.; Bandera, J.; and Marfil, R.\n\n\n \n\n\n\n In FinE-R 2015. The path to success: Failures in Real Robots, volume 1484, 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"Gualzru's$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Fernandez2015,\nabstract = {Copyright {\\textcopyright} 2015 for the individual papers by the papers' authors.This paper describes the genesis of Gualzru, a robot commissioned by a large Spanish technological company to provide advertisement services in open public spaces. Gualzru has to stand by at an interactive panel observing the people passing by and, at some point, select a promising candidate and approach her to initiate a conversation. After a small verbal interaction, the robot is supposed to convince the passerby to walk back to the panel, leaving the rest of the selling task to an interactive software embedded in it. The whole design and building process took less than three years of team composed of five groups at different geographical locations. We describe here the lessons learned during this period of time, from different points of view including the hardware, software, architectural decisions and team collaboration issues.},\nauthor = {Fern{\\'{a}}ndez, F. and Mart{\\'{i}}nez, M. and Garc{\\'{i}}a-Varea, I. and Mart{\\'{i}}nez-G{\\'{o}}mez, J. and P{\\'{e}}rez-Lorenzo, J.M. and Viciana, R. and Bustos, P. and Manso, L.J. and Calderita, L. and Guti{\\'{e}}rrez, M. and N{\\'{u}}{\\~{n}}ez, P. and Bandera, A. and Romero-Garc{\\'{e}}s, A. and Bandera, J.P. and Marfil, R.},\nbooktitle = {FinE-R 2015. The path to success: Failures in Real Robots},\nfile = {:home/fernando/papers/tmp/paper23.pdf:pdf},\nissn = {16130073},\ntitle = {{Gualzru's path to the advertisement world}},\nurl = {http://ceur-ws.org/Vol-1484/},\nvolume = {1484},\nyear = {2015}\n}\n

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\n \n\n \n \n \n \n \n \n Therapy Monitoring and Patient Evaluation with Social Robots.\n \n \n \n \n\n\n \n Martín, A.; González, J. C.; Pulido, J. C.; García-Olaya, Á.; Fernández, F.; and Suárez, C.\n\n\n \n\n\n\n In Proceedings of the 3rd 2015 Workshop on ICTs for improving Patients Rehabilitation Research Techniques - REHAB '15, volume 01-02-Octo, pages 152–155, New York, New York, USA, 2015. ACM Press\n \n\n\n\n
\n\n\n\n \n \n $\"Therapy$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@inproceedings{Martin2015,\nabstract = {{\\textcopyright} 2015 ACM.Social robots have a great potential. With high movement capabilities and large computational capacity, they allow to perform varied tasks that were usually conducted by humans. One of these tasks are physical therapies, where a therapist guides a patient through the realisation of a set of exercises. A robot, equipped with a sophisticated artificial vision system, can conduct these therapies and evaluate the patient movements. In this paper, we present a system that allows the therapist to design a complete therapy to be carried out by the robot, to start each session with the robot, to evaluate the patient condition over the therapy and to generate reports at the end of a session.},\naddress = {New York, New York, USA},\nauthor = {Mart{\\'{i}}n, Alejandro and Gonz{\\'{a}}lez, Jos{\\'{e}} C. and Pulido, Jos{\\'{e}} C. and Garc{\\'{i}}a-Olaya, {\\'{A}}ngel and Fern{\\'{a}}ndez, Fernando and Su{\\'{a}}rez, Cristina},\nbooktitle = {Proceedings of the 3rd 2015 Workshop on ICTs for improving Patients Rehabilitation Research Techniques - REHAB '15},\ndoi = {10.1145/2838944.2838981},\nfile = {:home/fernando/papers/tmp/p152-Martin.pdf:pdf},\nisbn = {9781450338981},\nkeywords = {Cerebral Palsy,QUEST,Social Robot,Therapy},\npages = {152--155},\npublisher = {ACM Press},\ntitle = {{Therapy Monitoring and Patient Evaluation with Social Robots}},\nurl = {http://dl.acm.org/citation.cfm?doid=2838944.2838981},\nvolume = {01-02-Octo},\nyear = {2015}\n}\n

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\n \n\n \n \n \n \n \n \n Asistente robótico socialmente interactivo para terapias de rehabilitación motriz con pacientes de pediatría.\n \n \n \n \n\n\n \n Calderita, L. V.; Bustos, P.; Suárez Mejías, C.; Fernández, F.; Viciana, R.; and Bandera, A.\n\n\n \n\n\n\n RIAI - Revista Iberoamericana de Automatica e Informatica Industrial, 12(1): 99–110. jan 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Asistente$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Calderita2015,\nabstract = {Motor rehabilitation therapy pursuits the recovery of damaged areas from the repetitive practice of certain motor activities. The patient's recovery directly depends on the adherence to rehabilitation therapy. Conventional methods consisting of repetitions usually make the patient feel unmotivated and neglect complying with the appropriate treatments. In addition, the treatment of these motor deficits requires intensive and extended rehabilitation sessions that demand sustained dedication and effort by professionals and incur in accretive costs for the institutions. Within this framework, this paper describes the development and evaluation of a new neurorehabilitation therapy, whose core is a socially interactive robot. This robot is able to consistently engaged patients in the therapeutic interaction, providing tireless motivation, encouragement and guidance. The experience has also been the origin of the design and implementation of a novel control architecture, RoboCog, which has provided the robot perceptual and cognitive capabilities that allow a behavior more socially developed, proactive. Verification tests carried out on the various components of the architecture show us the proper working of these and its integration with the rest of the architecture. Furthermore, this therapy has been successfully with congenital brachial palsy (PBO), a disease caused by damage acquired at birth and affects motor mobility of the upper limbs, but not their intellectual and communicative abilities.},\nauthor = {Calderita, L. V. and Bustos, P. and {Su{\\'{a}}rez Mej{\\'{i}}as}, C. and Fern{\\'{a}}ndez, F. and Viciana, R. and Bandera, A.},\ndoi = {10.1016/j.riai.2014.09.007},\nfile = {:home/fernando/papers/tmp/1-s2.0-S1697791214000879-main.pdf:pdf},\nissn = {16977920},\njournal = {RIAI - Revista Iberoamericana de Automatica e Informatica Industrial},\nkeywords = {Human-Robot Interaction,Rehabilitation therapies,Socially assistant robotics},\nmonth = {jan},\nnumber = {1},\npages = {99--110},\ntitle = {{Asistente rob{\\'{o}}tico socialmente interactivo para terapias de rehabilitaci{\\'{o}}n motriz con pacientes de pediatr{\\'{i}}a}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S1697791214000879},\nvolume = {12},\nyear = {2015}\n}\n

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\n \n\n \n \n \n \n \n \n Emergent Collective Behaviors in a Multi-agent Reinforcement Learning Pedestrian Simulation: A Case Study.\n \n \n \n \n\n\n \n Martinez-Gil, F.; Lozano, M.; and Fernández, F.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 9002, pages 228–238. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Emergent$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@incollection{Martinez-Gil2015,\nabstract = {{\\textcopyright} Springer International Publishing Switzerland 2015.In this work, a Multi-agent Reinforcement Learning framework is used to generate simulations of virtual pedestrians groups. The aim is to study the influence of two different learning approaches in the quality of generated simulations. The case of study consists on the simulation of the crossing of two groups of embodied virtual agents inside a narrow corridor. This scenario is a classic experiment inside the pedestrian modeling area, because a collective behavior, specifically the lanes formation, emerges with real pedestrians. The paper studies the influence of different learning algorithms, function approximation approaches, and knowledge transfer mechanisms on performance of learned pedestrian behaviors. Specifically, two different RL-based schemas are analyzed. The first one, Iterative Vector Quantization with Q-Learning (ITVQQL), improves iteratively a state-space generalizer based on vector quantization. The second scheme, named TS, uses tile coding as the generalization method with the Sarsa($\\lambda$) algorithm. Knowledge transfer approach is based on the use of Probabilistic Policy Reuse to incorporate previously acquired knowledge in current learning processes; additionally, value function transfer is also used in the ITVQQL schema to transfer the value function between consecutive iterations. Results demonstrate empirically that our RL framework generates individual behaviors capable of emerging the expected collective behavior as occurred in real pedestrians. This collective behavior appears independently of the learning algorithm and the generalization method used, but depends extremely on whether knowledge transfer was applied or not. In addition, the use of transfer techniques has a remarkable influence in the final performance (measured in number of times that the task was solved) of the learned behaviors.},\nauthor = {Martinez-Gil, Francisco and Lozano, Miguel and Fern{\\'{a}}ndez, Fernando},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\ndoi = {10.1007/978-3-319-14627-0_16},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F978-3-319-14627-0{\\_}16.pdf:pdf},\nisbn = {9783319146263},\nissn = {16113349},\nkeywords = {Pedestrians simulation,Policy Reus,Tile coding,Transfer learning,Vector Quantization},\npages = {228--238},\ntitle = {{Emergent Collective Behaviors in a Multi-agent Reinforcement Learning Pedestrian Simulation: A Case Study}},\nurl = {http://link.springer.com/10.1007/978-3-319-14627-0{\\_}16},\nvolume = {9002},\nyear = {2015}\n}\n

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\n \n\n \n \n \n \n \n \n Strategies for simulating pedestrian navigation with multiple reinforcement learning agents.\n \n \n \n \n\n\n \n Martinez-Gil, F.; Lozano, M.; and Fernández, F.\n\n\n \n\n\n\n Autonomous Agents and Multi-Agent Systems, 29(1): 98–130. jan 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Strategies$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Martinez-Gil2015a,\nabstract = {{\\textcopyright} 2014, The Author(s).In this paper, a new multi-agent reinforcement learning approach is introduced for the simulation of pedestrian groups. Unlike other solutions, where the behaviors of the pedestrians are coded in the system, in our approach the agents learn by interacting with the environment. The embodied agents must learn to control their velocity, avoiding obstacles and the other pedestrians, to reach a goal inside the scenario. The main contribution of this paper is to propose this new methodology that uses different iterative learning strategies, combining a vector quantization (state space generalization) with the Q-learning algorithm (VQQL). Two algorithmic schemas, Iterative VQQL and Incremental, which differ in the way of addressing the problems, have been designed and used with and without transfer of knowledge. These algorithms are tested and compared with the VQQL algorithm as a baseline in two scenarios where agents need to solve well-known problems in pedestrian modeling. In the first, agents in a closed room need to reach the unique exit producing and solving a bottleneck. In in the second, two groups of agents inside a corridor need to reach their goal that is placed in opposite sides (they need to solve the crossing). In the first scenario, we focus on scalability, use metrics from the pedestrian modeling field, and compare with the Helbing's social force model. The emergence of collective behaviors, that is, the shell-shaped clogging in front of the exit in the first scenario, and the lane formation as a solution to the problem of the crossing, have been obtained and analyzed. The results demonstrate that the proposed schemas find policies that carry out the tasks, suggesting that they are applicable and generalizable to the simulation of pedestrians groups.},\nauthor = {Martinez-Gil, Francisco and Lozano, Miguel and Fern{\\'{a}}ndez, Fernando},\ndoi = {10.1007/s10458-014-9252-6},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2Fs10458-014-9252-6.pdf:pdf},\nissn = {1387-2532},\njournal = {Autonomous Agents and Multi-Agent Systems},\nkeywords = {Collective behaviors,MARL,Pedestrian simulation,VQQL},\nmonth = {jan},\nnumber = {1},\npages = {98--130},\ntitle = {{Strategies for simulating pedestrian navigation with multiple reinforcement learning agents}},\nurl = {http://link.springer.com/10.1007/s10458-014-9252-6},\nvolume = {29},\nyear = {2015}\n}\n

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\n \n\n \n \n \n \n \n \n A comprehensive survey on safe reinforcement learning.\n \n \n \n \n\n\n \n García, J.; and Fernández, F.\n\n\n \n\n\n\n Journal of Machine Learning Research, 16: 1437–1480. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Garcia2015,\nabstract = {{\\textcopyright} 2015 Javier Gar{\\'{c}}ia and Fernando Fernandez.Safe Reinforcement Learning can be defined as the process of learning policies that maximize the expectation of the return in problems in which it is important to ensure reasonable system performance and/or respect safety constraints during the learning and/or deployment processes. We categorize and analyze two approaches of Safe Reinforcement Learning. The first is based on the modification of the optimality criterion, the classic discounted finite/infinite horizon, with a safety factor. The second is based on the modification of the exploration process through the incorporation of external knowledge or the guidance of a risk metric. We use the proposed classification to survey the existing literature, as well as suggesting future directions for Safe Reinforcement Learning.},\nauthor = {Garc{\\'{i}}a, J. and Fern{\\'{a}}ndez, F.},\nfile = {:home/fernando/papers/tmp/garcia15a.pdf:pdf},\nissn = {15337928},\njournal = {Journal of Machine Learning Research},\nkeywords = {Reinforcement learning,Risk sensitivity,Safe exploration,Teacher advice},\npages = {1437--1480},\ntitle = {{A comprehensive survey on safe reinforcement learning}},\nurl = {http://jmlr.org/papers/v16/garcia15a.html},\nvolume = {16},\nyear = {2015}\n}\n

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\n \n\n \n \n \n \n \n \n The deterministic part of the seventh International Planning Competition.\n \n \n \n \n\n\n \n Linares López, C.; Jiménez Celorrio, S.; and García-Olaya, A.\n\n\n \n\n\n\n Artificial Intelligence, 223: 82–119. jun 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{LinaresLopez2015,\nabstract = {The International Planning Competition is organized in the context of the International Conference on Automated Planning and Scheduling (ICAPS) and it is considered a reference source for the planning and scheduling community. The competition is typically organized every two years and deals with relevant issues for the community such as the definition of evaluation standards, the publication of benchmarks and the collection and dissemination of data about state-of-the-art planners. This paper focuses on the deterministic part, the longest-running part of the International Planning Competition. The paper describes its format, the participants, the selection of benchmarks and the generated results accompanied with analysis from different perspectives. The paper also examines the results of a brand new track created to explore the potential of planners that exploit the power of multi-core processors. Overall, the results of the competition indicate significant progress with respect to previous competitions, but they also reveal that some issues remain open and need further research, such as the coverage of temporal planners when concurrency is required and the performance in the multi-core track. As a novelty, all the data and the software generated for running the competition have been made publicly available allowing researchers to reproduce the competition and to carry out different analysis of the results.},\nauthor = {{Linares L{\\'{o}}pez}, Carlos and {Jim{\\'{e}}nez Celorrio}, Sergio and Garc{\\'{i}}a-Olaya, Angel},\ndoi = {10.1016/j.artint.2015.01.004},\nfile = {:C$\\backslash$:/Users/angel/Documents/Mendeley Desktop/Linares L{\\'{o}}pez, Jim{\\'{e}}nez Celorrio, Garc{\\'{i}}a-Olaya - 2015 - The deterministic part of the seventh International Planning Competition.pdf:pdf},\nissn = {00043702},\njournal = {Artificial Intelligence},\nkeywords = {Automated planning,Benchmarks for planning,Experimental evaluation of planning systems,International Planning Competition,Planning systems},\nmendeley-groups = {Papers/2018-IJCAI-Gotcha,Papers/2018-OSP},\nmonth = {jun},\npages = {82--119},\ntitle = {{The deterministic part of the seventh International Planning Competition}},\nurl = {http://www.sciencedirect.com/science/article/pii/S0004370215000144 http://linkinghub.elsevier.com/retrieve/pii/S0004370215000144},\nvolume = {223},\nyear = {2015}\n}\n

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\n \n\n \n \n \n \n \n \n Therapy Monitoring and Patient Evaluation with Social Robots.\n \n \n \n \n\n\n \n Martín, A.; González, J. C.; Pulido, J. C.; García-Olaya, A.; Fernández, F.; and Suárez, C.\n\n\n \n\n\n\n In Proceedings of the 3rd 2015 Workshop on ICTs for improving Patients Rehabilitation Research Techniques - REHAB '15, volume 01-02-Octo, pages 152–155, 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"Therapy$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@inproceedings{Martin2015,\nabstract = {{\\textcopyright} 2015 ACM.Social robots have a great potential. With high movement capabilities and large computational capacity, they allow to perform varied tasks that were usually conducted by humans. One of these tasks are physical therapies, where a therapist guides a patient through the realisation of a set of exercises. A robot, equipped with a sophisticated artificial vision system, can conduct these therapies and evaluate the patient movements. In this paper, we present a system that allows the therapist to design a complete therapy to be carried out by the robot, to start each session with the robot, to evaluate the patient condition over the therapy and to generate reports at the end of a session.},\nauthor = {Mart{\\'{i}}n, Alejandro and Gonz{\\'{a}}lez, Jos{\\'{e}} Carlos and Pulido, Jos{\\'{e}} Carlos and Garc{\\'{i}}a-Olaya, Angel and Fern{\\'{a}}ndez, Fernando and Su{\\'{a}}rez, Cristina},\nbooktitle = {Proceedings of the 3rd 2015 Workshop on ICTs for improving Patients Rehabilitation Research Techniques - REHAB '15},\ndoi = {10.1145/2838944.2838981},\nisbn = {9781450338981},\nkeywords = {Cerebral Palsy,QUEST,Social Robot,Therapy},\npages = {152--155},\ntitle = {{Therapy Monitoring and Patient Evaluation with Social Robots}},\nurl = {http://dl.acm.org/citation.cfm?doid=2838944.2838981},\nvolume = {01-02-Octo},\nyear = {2015}\n}\n

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\n \n\n \n \n \n \n \n \n Automatic construction of optimal static sequential portfolios for AI planning and beyond.\n \n \n \n \n\n\n \n Núñez, S.; Borrajo, D.; and Linares-López, C.\n\n\n \n\n\n\n Artificial Intelligence, 226: 75–101. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Automatic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aij15-portfolios,\n\n  author = {Sergio Núñez and Daniel Borrajo and Carlos Linares-López},\n\n  title = {Automatic construction of optimal static sequential portfolios for {AI} planning and beyond},\n\n  journal = {Artificial Intelligence},\n\n  year = {2015},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  jcr = {Q1, 2015: 3.333 (16/130)},\n\n  publisher = {Elsevier},\n\n  optdoi = {doi:10.1016/j.artint.2015.05.005},\n\n  optkey = {},\n\n  volume = {226},\n\n  url = {http://www.sciencedirect.com/science/article/pii/S000437021500079X},\n\n  optnumber = {},\n\n  optmonth = {September},\n\n  pages = {75--101},\n\n  optnote = {},\n\n  optannote = {ISSN: 0004-3702}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Sorting Sequential Portfolios in Automated Planning.\n \n \n \n \n\n\n \n Núñez, S.; Borrajo, D.; and Linares-López, C.\n\n\n \n\n\n\n In Proceedings of the IJCAI'15, Buenos Aires (Argentina), 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"Sorting$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ijcai15,\n\n  author = {Sergio Núñez and Daniel Borrajo and Carlos Linares-López},\n\n  title = {Sorting Sequential Portfolios in Automated Planning},\n\n  booktitle = {Proceedings of the IJCAI'15},\n\n  optcrossref = {},\n\n  opteditor = {},\n\n  url = {ijcai15.pdf},\n\n  year = {2015},\n\n  cicyt = {congresos-buenos},\n\n  jcr = {A*},\n\n  key = {Planning-Learning},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {Buenos Aires (Argentina)},\n\n  optmonth = {},\n\n  optpages = {},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using Random Sampling Trees for Automated Planning.\n \n \n \n \n\n\n \n Alcázar, V.; Fernández, S.; Borrajo, D.; and Veloso, M.\n\n\n \n\n\n\n AI Communications, 28(4): 665-681. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aicomm15-rpt,\n\n  author = {Vidal Alcázar and Susana Fernández and Daniel Borrajo and Manuela Veloso},\n\n  title = {Using Random Sampling Trees for Automated Planning},\n\n  journal = {AI Communications},\n\n  volume = {28},\n\n  number = {4},\n\n  year = {2015},\n\n  url = {http://content.iospress.com/articles/ai-communications/aic658},\n\n  publisher = {IOS Press},\n\n  address = {},\n\n  key = {Planning-Learning},\n\n  month = {},\n\n  pages = {665-681},\n\n  cicyt = {revista},\n\n  jcr = {Q4, 2015: 0.364 (126/130)},\n\n  optnote = {},\n\n  issn = {ISSN on-line: 1875-8452},\n\n  optannote = {3-Feb-2014}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Progress in Case-Based Planning.\n \n \n \n \n\n\n \n Borrajo, D.; Roubíčková, A.; and Serina, I.\n\n\n \n\n\n\n ACM Computing Surveys, 47(2): 35:1–35:39. January 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Progress$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{acmsurvey15,\n\n  author = {Daniel Borrajo and Anna Roubí\\v{c}kov\\'a and Ivan Serina},\n\n  title = {Progress in Case-Based Planning},\n\n  journal = {ACM Computing Surveys},\n\n  year = {2015},\n\n  url = {acm-survey.pdf},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  jcr = {Q1, Categoría: Computer science, theory \\& methods 2015: 5.243 (2/105)},\n\n  publisher = {ACM},\n\n  volume = {47},\n\n  number = {2},\n\n  month = {January},\n\n  pages = {35:1--35:39},\n\n  doi = {10.1145/2674024},\n\n  issn = {0360-0300},\n\n  optannote = {4-Feb-2014, 16-May-2014, 18-Aug-2014}\n\n}\n\n\n\n

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\n \n 2014\n \n \n (7)\n \n \n

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\n \n\n \n \n \n \n \n \n Solving the Target-Value Search Problem.\n \n \n \n \n\n\n \n Linares López, C.; Stern, R.; and Felner, A.\n\n\n \n\n\n\n In Proceedings of the Seventh International Symposium on Combinatorial Search (SoCS 2014), pages 202–203, Prague, Czech Republic, August 2014. \n \n\n\n\n
\n\n\n\n \n \n $\"Solving$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c.stern.r.ea:solving,\n  author\t= {Carlos {Linares L\\'opez} and Roni Stern and Ariel Felner},\n  title\t\t= {Solving the Target-Value Search Problem},\n  booktitle\t= {Proceedings of the Seventh International Symposium on\n\t\t  Combinatorial Search (SoCS 2014)},\n  pages\t\t= {202--203},\n  year\t\t= {2014},\n  address\t= {Prague, Czech Republic},\n  month\t\t= aug,\n  url\t\t= {http://www.aaai.org/ocs/index.php/SOCS/SOCS14/paper/view/8923}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n THERAPIST:Towards an autonomous socially interactive robot for motor and neurorehabilitation therapies for children.\n \n \n \n \n\n\n \n Calderita, L.; Manso, L.; Bustos, P.; Suárez-Mejías, C.; Fernández, F.; and Bandera, A.\n\n\n \n\n\n\n JMIR Rehabilitation and Assistive Technologies, 1(1). 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"THERAPIST:Towards$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Calderita2014,\nabstract = {Neurorehabilitation therapies exploiting the use-dependent plasticity of our neuromuscular system are devised to help patients who suffer from injuries or diseases of this system. These therapies take advantage of the fact that the motor activity alters the properties of our neurons and muscles, including the pattern of their connectivity, and thus their functionality. Hence, a sensor-motor treatment where patients makes certain movements will help them (re)learn how to move the affected body parts. But these traditional rehabilitation processes are usually repetitive and lengthy, reducing motivation and adherence to the treatment, and thus limiting the benefits for the patients. Objective: Our goal was to create innovative neurorehabilitation therapies based on THERAPIST, a socially assistive robot. THERAPIST is an autonomous robot that is able to find and execute plans and adapt them to new situations in real-time. The software architecture of THERAPIST monitors and determines the course of action, learns from previous experiences, and interacts with people using verbal and non-verbal channels. THERAPIST can increase the adherence of the patient to the sessions using serious games. Data are recorded and can be used to tailor patient sessions. Methods: We hypothesized that pediatric patients would engage better in a therapeutic non-physical interaction with a robot, facilitating the design of new therapies to improve patient motivation. We propose RoboCog, a novel cognitive architecture. This architecture will enhance the effectiveness and time-of-response of complex multi-degree-of-freedom robots designed to collaborate with humans, combining two core elements: a deep and hybrid representation of the current state, own, and observed; and a set of task-dependent planners, working at different levels of abstraction but connected to this central representation through a common interface. Using RoboCog, THERAPIST engages the human partner in an active interactive process. But RoboCog also endows the robot with abilities for high-level planning, monitoring, and learning. Thus, THERAPIST engages the patient through different games or activities, and adapts the session to each individual. Results: RoboCog successfully integrates a deliberative planner with a set of modules working at situational or sensorimotor levels. This architecture also allows THERAPIST to deliver responses at a human rate. The synchronization of the multiple interaction modalities results from a unique scene representation or model. THERAPIST is now a socially interactive robot that, instead of reproducing the phrases or gestures that the developers decide, maintains a dialogue and autonomously generate gestures or expressions. THERAPIST is able to play simple games with human partners, which requires humans to perform certain movements, and also to capture the human motion, for later analysis by clinic specialists. Conclusions: The initial hypothesis was validated by our experimental studies showing that interaction with the robot results in highly attentive and collaborative attitudes in pediatric patients. We also verified that RoboCog allows the robot to interact with patients at human rates. However, there remain many issues to overcome. The development of novel hands-off rehabilitation therapies will require the intersection of multiple challenging directions of research that we are currently exploring.},\nauthor = {Calderita, L.V. and Manso, L.J. and Bustos, P. and Su{\\'{a}}rez-Mej{\\'{i}}as, C. and Fern{\\'{a}}ndez, F. and Bandera, A.},\ndoi = {10.2196/rehab.3151},\nissn = {14388871},\njournal = {JMIR Rehabilitation and Assistive Technologies},\nkeywords = {Cognitive robotics,Interactive games,Rehabilitation},\nnumber = {1},\ntitle = {{THERAPIST:Towards an autonomous socially interactive robot for motor and neurorehabilitation therapies for children}},\nurl = {https://rehab.jmir.org/2014/1/e1/},\nvolume = {1},\nyear = {2014}\n}\n

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\n Neurorehabilitation therapies exploiting the use-dependent plasticity of our neuromuscular system are devised to help patients who suffer from injuries or diseases of this system. These therapies take advantage of the fact that the motor activity alters the properties of our neurons and muscles, including the pattern of their connectivity, and thus their functionality. Hence, a sensor-motor treatment where patients makes certain movements will help them (re)learn how to move the affected body parts. But these traditional rehabilitation processes are usually repetitive and lengthy, reducing motivation and adherence to the treatment, and thus limiting the benefits for the patients. Objective: Our goal was to create innovative neurorehabilitation therapies based on THERAPIST, a socially assistive robot. THERAPIST is an autonomous robot that is able to find and execute plans and adapt them to new situations in real-time. The software architecture of THERAPIST monitors and determines the course of action, learns from previous experiences, and interacts with people using verbal and non-verbal channels. THERAPIST can increase the adherence of the patient to the sessions using serious games. Data are recorded and can be used to tailor patient sessions. Methods: We hypothesized that pediatric patients would engage better in a therapeutic non-physical interaction with a robot, facilitating the design of new therapies to improve patient motivation. We propose RoboCog, a novel cognitive architecture. This architecture will enhance the effectiveness and time-of-response of complex multi-degree-of-freedom robots designed to collaborate with humans, combining two core elements: a deep and hybrid representation of the current state, own, and observed; and a set of task-dependent planners, working at different levels of abstraction but connected to this central representation through a common interface. Using RoboCog, THERAPIST engages the human partner in an active interactive process. But RoboCog also endows the robot with abilities for high-level planning, monitoring, and learning. Thus, THERAPIST engages the patient through different games or activities, and adapts the session to each individual. Results: RoboCog successfully integrates a deliberative planner with a set of modules working at situational or sensorimotor levels. This architecture also allows THERAPIST to deliver responses at a human rate. The synchronization of the multiple interaction modalities results from a unique scene representation or model. THERAPIST is now a socially interactive robot that, instead of reproducing the phrases or gestures that the developers decide, maintains a dialogue and autonomously generate gestures or expressions. THERAPIST is able to play simple games with human partners, which requires humans to perform certain movements, and also to capture the human motion, for later analysis by clinic specialists. Conclusions: The initial hypothesis was validated by our experimental studies showing that interaction with the robot results in highly attentive and collaborative attitudes in pediatric patients. We also verified that RoboCog allows the robot to interact with patients at human rates. However, there remain many issues to overcome. The development of novel hands-off rehabilitation therapies will require the intersection of multiple challenging directions of research that we are currently exploring.\n

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\n \n\n \n \n \n \n \n \n MARL-Ped: A multi-agent reinforcement learning based framework to simulate pedestrian groups.\n \n \n \n \n\n\n \n Martinez-Gil, F.; Lozano, M.; and Fern?ndez, F.\n\n\n \n\n\n\n Simulation Modelling Practice and Theory, 47: 259–275. sep 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"MARL-Ped:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Martinez-Gil2014,\nabstract = {Pedestrian simulation is complex because there are different levels of behavior modeling. At the lowest level, local interactions between agents occur; at the middle level, strategic and tactical behaviors appear like overtakings or route choices; and at the highest level path-planning is necessary. The agent-based pedestrian simulators either focus on a specific level (mainly in the lower one) or define strategies like the layered architectures to independently manage the different behavioral levels. In our Multi-Agent Reinforcement-Learning-based Pedestrian simulation framework (MARL-Ped) the situation is addressed as a whole. Each embodied agent uses a model-free Reinforcement Learning (RL) algorithm to learn autonomously to navigate in the virtual environment. The main goal of this work is to demonstrate empirically that MARL-Ped generates learned behaviors adapted to the level required by the pedestrian scenario. Three different experiments, described in the pedestrian modeling literature, are presented to test our approach: (i) election of the shortest path vs. quickest path; (ii) a crossing between two groups of pedestrians walking in opposite directions inside a narrow corridor; (iii) two agents that move in opposite directions inside a maze. The results show that MARL-Ped solves the different problems, learning individual behaviors with characteristics of pedestrians (local control that produces adequate fundamental diagrams, route-choice capability, emergence of collective behaviors and path-planning). Besides, we compared our model with that of Helbing's social forces, a well-known model of pedestrians, showing similarities between the pedestrian dynamics generated by both approaches. These results demonstrate empirically that MARL-Ped generates variate plausible behaviors, producing human-like macroscopic pedestrian flow. {\\textcopyright} 2014 Elsevier B.V. All rights reserved.},\nauthor = {Martinez-Gil, Francisco and Lozano, Miguel and Fern?ndez, Fernando},\ndoi = {10.1016/j.simpat.2014.06.005},\nfile = {:home/fernando/papers/tmp/1-s2.0-S1569190X14000999-main.pdf:pdf},\nissn = {1569190X},\njournal = {Simulation Modelling Practice and Theory},\nkeywords = {Path-planning,Route-choice,Sarsa($\\lambda$)},\nmonth = {sep},\npages = {259--275},\ntitle = {{MARL-Ped: A multi-agent reinforcement learning based framework to simulate pedestrian groups}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S1569190X14000999},\nvolume = {47},\nyear = {2014}\n}\n

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\n \n\n \n \n \n \n \n Multi-Agent Planning with Agent Preferences.\n \n \n \n\n\n \n Virseda, J.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the 2nd ICAPS Distributed and Multi-Agent Planning Workshop (DMAP-2014), pages 70–78, Portsmouth, NH (USA), 2014. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 5 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{dmap14-preferences,\n\n  author = {Jesús Virseda and Susana Fernández and Daniel Borrajo},\n\n  booktitle = {Proceedings of the 2nd ICAPS Distributed and Multi-Agent Planning Workshop (DMAP-2014)},\n\n  title = {Multi-Agent Planning with Agent Preferences},\n\n  year = {2014},\n\n  key = {Planning-Learning},\n\n  myurl = {http://icaps14.icaps-conference.org/proceedings/dmap/DMAP_proceedings.pdf},\n\n  opteditor = {Daniel Borrajo and Daniel L. Kovacs and Alejandro Torreño},\n\n  address = {Portsmouth, NH (USA)},\n\n  pages = {70--78},\n\n  cicyt = {workshops},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Plan Merging by Reuse for Multi-Agent Planning.\n \n \n \n\n\n \n Luis, N.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the 2nd ICAPS Distributed and Multi-Agent Planning Workshop (DMAP-2014), pages 38–44, Portsmouth, NH (USA), 2014. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{dmap14-plan-merging,\n\n  author = {Nerea Luis and Daniel Borrajo},\n\n  booktitle = {Proceedings of the 2nd ICAPS Distributed and Multi-Agent Planning Workshop (DMAP-2014)},\n\n  title = {Plan Merging by Reuse for Multi-Agent Planning},\n\n  year = {2014},\n\n  key = {Planning-Learning},\n\n  myurl = {http://icaps14.icaps-conference.org/proceedings/dmap/DMAP_proceedings.pdf},\n\n  opteditor = {Daniel Borrajo and Daniel L. Kovacs and Alejandro Torreño},\n\n  volume = {},\n\n  series = {},\n\n  address = {Portsmouth, NH (USA)},\n\n  pages = {38--44},\n\n  cicyt = {workshops},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Analyzing the Impact of Partial States on Duplicate Detection and Collision of Frontiers.\n \n \n \n \n\n\n \n Alcázar, V.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of ICAPS'14, pages 350–354, Portsmouth (EEUU), 2014. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Analyzing$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icaps14,\n\n  author = {Vidal Alcázar and Susana Fernández and Daniel Borrajo},\n\n  title = {Analyzing the Impact of Partial States on Duplicate Detection and Collision of Frontiers},\n\n  booktitle = {Proceedings of ICAPS'14},\n\n  optcrossref = {},\n\n  optkey = {},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  url = {icaps14.pdf},\n\n  year = {2014},\n\n  cicyt = {congresos-buenos},\n\n  key = {Planning-Learning},\n\n  jcr = {A*},\n\n  optorganization = {},\n\n  publisher = {AAAI Press},\n\n  address = {Portsmouth (EEUU)},\n\n  optmonth = {},\n\n  pages = {350--354},\n\n  optnote = {},\n\n  optannote = {the 24th International Conference on Automated Planning and Scheduling}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Flexible Integration of Planning and Information Gathering.\n \n \n \n \n\n\n \n Camacho, D.; Borrajo, D.; Molina, J. M.; and Aler, R.\n\n\n \n\n\n\n In Cesta, A.; and Borrajo, D., editor(s), Proceedings of the Sixth European Conference on Planning (ECP'01), pages 10–16, Toledo (Spain), September 2014. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Flexible$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ecp01,\n\n  author = {David Camacho and Daniel Borrajo and José Manuel Molina and Ricardo Aler},\n\n  title = {Flexible Integration of Planning and Information Gathering},\n\n  booktitle = {{Proceedings of the Sixth European Conference on Planning (ECP'01)}},\n\n  editor = {Amedeo Cesta and Daniel Borrajo},\n\n  year = {2014},\n\n  url = {http://www.aaai.org/ocs/index.php/ECP/ECP01/paper/view/7324},\n\n  publisher = {AAAI Press},\n\n  cicyt = {congresos-buenos},\n\n  volumen = {},\n\n  address = {Toledo (Spain)},\n\n  month = {September},\n\n  key = {Planning-Web},\n\n  pages = {10--16},\n\n  jcr = {A* (predecesor de ICAPS)}\n\n}\n\n\n\n

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\n \n 2013\n \n \n (23)\n \n \n

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\n \n\n \n \n \n \n \n \n Multi-step Generation of Bayesian Networks Models for Software Projects Estimations.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; Linares López, C.; and Ocón, J.\n\n\n \n\n\n\n International Journal of Computational Intelligence Systems , 6(5): 796–821. May 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Multi-step$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 18 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@Article{\t  fuentetaja.r.borrajo.d.ea:multi-step,\n  author\t= {Raquel Fuentetaja and Daniel Borrajo and Carlos {Linares\n\t\t  L\\'opez} and Jorge Oc\\'on},\n  title\t\t= {Multi-step Generation of Bayesian Networks Models for\n\t\t  Software Projects Estimations},\n  journal\t= {International Journal of Computational Intelligence\n\t\t  Systems },\n  year\t\t= {2013},\n  volume\t= 6,\n  number\t= 5,\n  pages\t\t= {796--821},\n  month\t\t= may,\n  url\t\t= {http://www.tandfonline.com/eprint/hHvBqUUDb4fi6q9qd6WN/full}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n Automating the evaluation of planning systems.\n \n \n \n\n\n \n Linares López, C.; Jiménez, S.; and Helmert, M.\n\n\n \n\n\n\n AI Communications, 26(4): 331–354. 2013.\n \n\n\n\n
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@Article{\t  linares-lopez.c.jimenez.s.ea:automating,\n  author\t= {Carlos {Linares L\\'opez} and Sergio Jim\\'enez and Malte\n\t\t  Helmert},\n  title\t\t= {Automating the evaluation of planning systems},\n  journal\t= {AI Communications},\n  year\t\t= 2013,\n  volume\t= 26,\n  number\t= 4,\n  pages\t\t= {331--354}\n}\n\n

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\n \n\n \n \n \n \n \n \n Target-Value Search Revisited (Extended Abstract).\n \n \n \n \n\n\n \n Linares López, C.; Stern, R.; and Felner, A.\n\n\n \n\n\n\n In Proceedings of the Sixth International Symposium on Combinatorial Search (SoCS 2013), pages 216–217, Seattle, Washington (United States), July 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"Target-Value$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c.stern.r.ea:target-value,\n  author\t= {Carlos {Linares L\\'opez} and Roni Stern and Ariel Felner},\n  title\t\t= {Target-Value Search Revisited (Extended Abstract)},\n  booktitle\t= {Proceedings of the Sixth International Symposium on\n\t\t  Combinatorial Search (SoCS 2013)},\n  pages\t\t= {216--217},\n  year\t\t= {2013},\n  address\t= {Seattle, Washington (United States)},\n  month\t\t= jul,\n  url\t\t= {http://www.aaai.org/Library/SOCS/socs13contents.php}\n}\n\n

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\n \n\n \n \n \n \n \n \n Symbolic Merge-and-Shrink for Cost-Optimal Planning.\n \n \n \n \n\n\n \n Torralba, Á.; Linares López, C.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI 2013), pages 2394–2400, Beijing (China), August 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  torralba.linares-lopez.c.ea:symbolic,\n  author\t= {Álvaro Torralba and Carlos {Linares L\\'opez} and Daniel\n\t\t  Borrajo},\n  title\t\t= {Symbolic Merge-and-Shrink for Cost-Optimal Planning},\n  booktitle\t= {Proceedings of the Twenty-Third International Joint\n\t\t  Conference on Artificial Intelligence (IJCAI 2013)},\n  pages\t\t= {2394--2400},\n  year\t\t= {2013},\n  address\t= {Beijing (China)},\n  month\t\t= aug,\n  url\t\t= {http://ijcai.org/papers13/Papers/IJCAI13-352.pdf}\n}\n\n

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\n \n\n \n \n \n \n \n \n Using automated planning for improving data mining processes.\n \n \n \n \n\n\n \n Fernández, S.; de la Rosa, T.; Fernández, F.; Suárez, R.; Ortiz, J.; Borrajo, D.; and Manzano, D.\n\n\n \n\n\n\n The Knowledge Engineering Review, 28(02): 157–173. jun 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Fernandez2013,\nabstract = {Abstract This paper presents a distributed architecture for automating data mining (DM) processes using standard languages. DM is a difficult task that relies on an exploratory and analytic process of processing large quantities of data in order to discover meaningful patterns. The increasing heterogeneity and complexity of available data requires some expert knowledge on how to combine the multiple and alternative DM tasks to process the data. Here, we describe DM tasks in terms of Automated Planning, which allows us to automate the DM knowledge flow construction. The work is based on the use of standards that have been defined in both DM and automated-planning communities. Thus, we use PMML (Predictive Model Markup Language) to describe DM tasks. From the PMML, a problem description in PDDL (Planning Domain Definition Language) can be generated, so any current planning system can be used to generate a plan. This plan is, again, translated to a DM workflow description, Knowledge Flow for Machine Learning format (Knowledge Flow file for the WEKA (Waikato Environment for Knowledge Analysis) tool), so the plan or DM workflow can be executed in WEKA. Copyright {\\textcopyright} Cambridge University Press 2013.},\nauthor = {Fern{\\'{a}}ndez, Susana and de la Rosa, Tom{\\'{a}}s and Fern{\\'{a}}ndez, Fernando and Su{\\'{a}}rez, Rub{\\'{e}}n and Ortiz, Javier and Borrajo, Daniel and Manzano, David},\ndoi = {10.1017/S0269888912000409},\nfile = {:home/fernando/papers/tmp/using{\\_}automated{\\_}planning{\\_}for{\\_}improving{\\_}data{\\_}mining{\\_}processes.pdf:pdf},\nissn = {0269-8889},\njournal = {The Knowledge Engineering Review},\nmonth = {jun},\nnumber = {02},\npages = {157--173},\ntitle = {{Using automated planning for improving data mining processes}},\nurl = {http://www.journals.cambridge.org/abstract{\\_}S0269888912000409},\nvolume = {28},\nyear = {2013}\n}\n

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\n \n\n \n \n \n \n \n \n Teaching Human Poses Interactively to a Social Robot.\n \n \n \n \n\n\n \n Gonzalez-Pacheco, V.; Malfaz, M.; Fernandez, F.; and Salichs, M.\n\n\n \n\n\n\n Sensors, 13(9): 12406–12430. sep 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Teaching$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Gonzalez-Pacheco2013,\nabstract = {The main activity of social robots is to interact with people. In order to do that, the robot must be able to understand what the user is saying or doing. Typically, this capability consists of pre-programmed behaviors or is acquired through controlled learning processes, which are executed before the social interaction begins. This paper presents a software architecture that enables a robot to learn poses in a similar way as people do. That is, hearing its teacher's explanations and acquiring new knowledge in real time. The architecture leans on two main components: an RGB-D (Red-, Green-, Blue- Depth) -based visual system, which gathers the user examples, and an Automatic Speech Recognition (ASR) system, which processes the speech describing those examples. The robot is able to naturally learn the poses the teacher is showing to it by maintaining a natural interaction with the teacher. We evaluate our system with 24 users who teach the robot a predetermined set of poses. The experimental results show that, with a few training examples, the system reaches high accuracy and robustness. This method shows how to combine data from the visual and auditory systems for the acquisition of new knowledge in a natural manner. Such a natural way of training enables robots to learn from users, even if they are not experts in robotics. {\\textcopyright} 2013 by the authors; licensee MDPI, Basel, Switzerland.},\nauthor = {Gonzalez-Pacheco, Victor and Malfaz, Maria and Fernandez, Fernando and Salichs, Miguel},\ndoi = {10.3390/s130912406},\nfile = {:home/fernando/papers/tmp/sensors-13-12406 (1).pdf:pdf},\nissn = {1424-8220},\njournal = {Sensors},\nkeywords = {Human-robot interaction,Interactive learning,Robot learning},\nmonth = {sep},\nnumber = {9},\npages = {12406--12430},\ntitle = {{Teaching Human Poses Interactively to a Social Robot}},\nurl = {http://www.mdpi.com/1424-8220/13/9/12406/},\nvolume = {13},\nyear = {2013}\n}\n

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\n \n\n \n \n \n \n \n \n INTEGRATING PLANNING, EXECUTION, AND LEARNING TO IMPROVE PLAN EXECUTION.\n \n \n \n \n\n\n \n Jim?nez, S.; Fern?ndez, F.; and Borrajo, D.\n\n\n \n\n\n\n Computational Intelligence, 29(1): 1–36. feb 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"INTEGRATING$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Jim?nez2013,\nabstract = {Algorithms for planning under uncertainty require accurate action models that explicitly capture the uncertainty of the environment. Unfortunately, obtaining these models is usually complex. In environments with uncertainty, actions may produce countless outcomes and hence, specifying them and their probability is a hard task. As a consequence, when implementing agents with planning capabilities, practitioners frequently opt for architectures that interleave classical planning and execution monitoring following a replanning when failure paradigm. Though this approach is more practical, it may produce fragile plans that need continuous replanning episodes or even worse, that result in execution dead-ends. In this paper, we propose a new architecture to relieve these shortcomings. The architecture is based on the integration of a relational learning component and the traditional planning and execution monitoring components. The new component allows the architecture to learn probabilistic rules of the success of actions from the execution of plans and to automatically upgrade the planning model with these rules. The upgraded models can be used by any classical planner that handles metric functions or, alternatively, by any probabilistic planner. This architecture proposal is designed to integrate off-the-shelf interchangeable planning and learning components so it can profit from the last advances in both fields without modifying the architecture. {\\textcopyright} 2012 Wiley Periodicals, Inc.},\nauthor = {Jim?nez, Sergio and Fern?ndez, Fernando and Borrajo, Daniel},\ndoi = {10.1111/j.1467-8640.2012.00447.x},\nfile = {:home/fernando/papers/tmp/Jim-nez{\\_}et{\\_}al-2013-Computational{\\_}Intelligence.pdf:pdf},\nissn = {08247935},\njournal = {Computational Intelligence},\nkeywords = {cognitive architectures,relational reinforcement learning,symbolic planning},\nmonth = {feb},\nnumber = {1},\npages = {1--36},\ntitle = {{INTEGRATING PLANNING, EXECUTION, AND LEARNING TO IMPROVE PLAN EXECUTION}},\nurl = {http://doi.wiley.com/10.1111/j.1467-8640.2012.00447.x},\nvolume = {29},\nyear = {2013}\n}\n

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\n \n\n \n \n \n \n \n \n From perception to action and vice versa: A new architecture showing how perception and action can modulate each other simultaneously.\n \n \n \n \n\n\n \n Palomino, A. J.; Garcia-Olaya, A.; Fernandez, F.; and Bandera, J. P.\n\n\n \n\n\n\n In 2013 European Conference on Mobile Robots, pages 268–273, sep 2013. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"From$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Palomino2013,\nabstract = {Artificial vision systems can not process all the information that they receive from the world in real time because it is highly expensive and inefficient in terms of computational cost. However, inspired by biological perception systems, it is possible to develop an artificial attention model able to select only the relevant part of the scene, as human vision does. From the Automated Planning point of view, a relevant area can be seen as an area where the objects involved in the execution of a plan are located. Thus, the planning system should guide the attention model to track relevant objects. But, at the same time, the perceived objects may constrain or provide new information that could suggest the modification of a current plan. Therefore, a plan that is being executed should be adapted or recomputed taking into account actual information perceived from the world. In this work, we introduce an architecture that creates a symbiosis between the planning and the attention modules of a robotic system, linking visual features with high level behaviours. The architecture is based on the interaction of an oversubscription planner, that produces plans constrained by the information perceived from the vision system, and an object-based attention system, able to focus on the relevant objects of the plan being executed. {\\textcopyright} 2013 IEEE.},\nauthor = {Palomino, Antonio Jesus and Garcia-Olaya, Angel and Fernandez, Fernando and Bandera, Juan Pedro},\nbooktitle = {2013 European Conference on Mobile Robots},\ndoi = {10.1109/ECMR.2013.6698853},\nfile = {:home/fernando/papers/tmp/06698853.pdf:pdf},\nisbn = {978-1-4799-0263-7},\nmonth = {sep},\npages = {268--273},\npublisher = {IEEE},\ntitle = {{From perception to action and vice versa: A new architecture showing how perception and action can modulate each other simultaneously}},\nurl = {http://ieeexplore.ieee.org/document/6698853/},\nyear = {2013}\n}\n

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\n \n\n \n \n \n \n \n \n Teaching Human Poses Interactively to a Social Robot.\n \n \n \n \n\n\n \n Gonzalez-Pacheco, V.; Malfaz, M.; Fernandez, F.; and Salichs, M.\n\n\n \n\n\n\n Sensors, 13(9): 12406–12430. sep 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Teaching$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Gonzalez-Pacheco2013a,\nabstract = {The main activity of social robots is to interact with people. In order to do that, the robot must be able to understand what the user is saying or doing. Typically, this capability consists of pre-programmed behaviors or is acquired through controlled learning processes, which are executed before the social interaction begins. This paper presents a software architecture that enables a robot to learn poses in a similar way as people do. That is, hearing its teacher's explanations and acquiring new knowledge in real time. The architecture leans on two main components: an RGB-D (Red-, Green-, Blue- Depth) -based visual system, which gathers the user examples, and an Automatic Speech Recognition (ASR) system, which processes the speech describing those examples. The robot is able to naturally learn the poses the teacher is showing to it by maintaining a natural interaction with the teacher. We evaluate our system with 24 users who teach the robot a predetermined set of poses. The experimental results show that, with a few training examples, the system reaches high accuracy and robustness. This method shows how to combine data from the visual and auditory systems for the acquisition of new knowledge in a natural manner. Such a natural way of training enables robots to learn from users, even if they are not experts in robotics.},\nauthor = {Gonzalez-Pacheco, Victor and Malfaz, Maria and Fernandez, Fernando and Salichs, Miguel},\ndoi = {10.3390/s130912406},\nfile = {:home/fernando/papers/tmp/sensors-13-12406 (1).pdf:pdf},\nissn = {1424-8220},\njournal = {Sensors},\nmonth = {sep},\nnumber = {9},\npages = {12406--12430},\ntitle = {{Teaching Human Poses Interactively to a Social Robot}},\nurl = {http://www.mdpi.com/1424-8220/13/9/12406/},\nvolume = {13},\nyear = {2013}\n}\n

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\n \n\n \n \n \n \n \n THERAPIST: Towards an autonomous socially interactive robot for motor and neurorehabilitation therapies for children.\n \n \n \n\n\n \n Calderita, L.; Bustos, P.; Suarez Mejias, C.; Fernández, F.; and Bandera, A.\n\n\n \n\n\n\n In Proceedings of the 2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, PervasiveHealth 2013, 2013. \n \n\n\n\n
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@inproceedings{Calderita2013,\nabstract = {Exploiting the use-dependent plasticity of our neuromuscular system, neuro-rehabilitation therapies are devised to help patients that suffer from injuries or diseases in this system, such as those caused by brain damage before or during birth or in the first years of life (e.g. due to cerebral palsy or obstetric brachial plexus palsy). These therapies take advantage of the fact that the motor activity alters the properties of our neurons and muscles, including the pattern of their connectivity, and thus their functionality. Hence, a sensor-motor treatment where the patient makes certain movements, will help her to (re)learn how to move the affected body parts. But this traditional rehabilitation processes come at a cost: therapies are usually repetitive and lengthy, reducing motivation and adherence to the treatment and thus limiting the benefits for the patients. This paper describes the motivation, experiences and current efforts towards the final development of THERAPIST, a socially interactive robot for neuro-rehabilitation assistance. Our starting hypothesis was that patients could get consistently engaged in a therapeutic non-physical interaction with a robot, facilitating the design of new therapies that should improve the patient recovery time and reduce the overall socio-economic costs. This hypothesis was validated by our initial experimental studies, which showed that pediatric patients can be easily driven into highly attentive and collaborating attitudes by letting them interact with a robot. However, in order to be safe and robust, this robot was teleoperated, requiring a great effort on supervision from clinic professionals. The development of a real socially interactive robot will require the intersection of multiple challenging directions of research that we are currently exploring. {\\textcopyright} 2013 ICST.},\nauthor = {Calderita, L.V. and Bustos, P. and {Suarez Mejias}, C. and Fern{\\'{a}}ndez, Fernando and Bandera, A.},\nbooktitle = {Proceedings of the 2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, PervasiveHealth 2013},\ndoi = {10.4108/icst.pervasivehealth.2013.252348},\nisbn = {9781936968800},\ntitle = {{THERAPIST: Towards an autonomous socially interactive robot for motor and neurorehabilitation therapies for children}},\nyear = {2013}\n}\n

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\n \n\n \n \n \n \n \n \n From perception to action and vice versa: A new architecture showing how perception and action can modulate each other simultaneously.\n \n \n \n \n\n\n \n Palomino, A. J.; Garcia-Olaya, A.; Fernandez, F.; and Bandera, J. P.\n\n\n \n\n\n\n In 2013 European Conference on Mobile Robots, ECMR 2013, pages 268–273, 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"From$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Palomino2013,\nabstract = {Artificial vision systems can not process all the information that they receive from the world in real time because it is highly expensive and inefficient in terms of computational cost. However, inspired by biological perception systems, it is possible to develop an artificial attention model able to select only the relevant part of the scene, as human vision does. From the Automated Planning point of view, a relevant area can be seen as an area where the objects involved in the execution of a plan are located. Thus, the planning system should guide the attention model to track relevant objects. But, at the same time, the perceived objects may constrain or provide new information that could suggest the modification of a current plan. Therefore, a plan that is being executed should be adapted or recomputed taking into account actual information perceived from the world. In this work, we introduce an architecture that creates a symbiosis between the planning and the attention modules of a robotic system, linking visual features with high level behaviours. The architecture is based on the interaction of an oversubscription planner, that produces plans constrained by the information perceived from the vision system, and an object-based attention system, able to focus on the relevant objects of the plan being executed. {\\textcopyright} 2013 IEEE.},\nauthor = {Palomino, Antonio Jesus and Garcia-Olaya, Angel and Fernandez, Fernando and Bandera, Juan Pedro},\nbooktitle = {2013 European Conference on Mobile Robots, ECMR 2013},\ndoi = {10.1109/ECMR.2013.6698853},\nisbn = {9781479902637},\npages = {268--273},\ntitle = {{From perception to action and vice versa: A new architecture showing how perception and action can modulate each other simultaneously}},\nurl = {http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2{\\&}SrcAuth=ORCID{\\&}SrcApp=OrcidOrg{\\&}DestLinkType=FullRecord{\\&}DestApp=WOS{\\_}CPL{\\&}KeyUT=WOS:000330234600043{\\&}KeyUID=WOS:000330234600043},\nyear = {2013}\n}\n

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\n \n\n \n \n \n \n \n \n Selective Abstraction in Automated Planning.\n \n \n \n \n\n\n \n Martínez, M.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of Second Annual Conference on Advances in Cognitive Systems (Cogsys), pages 133-147, Baltimore (EEUU), 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"Selective$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{cogsys13,\n\n  author = {Moisés Martínez and Fernando Fernández and Daniel Borrajo},\n\n  title = {Selective Abstraction in Automated Planning},\n\n  booktitle = {Proceedings of Second Annual Conference on Advances in Cognitive Systems (Cogsys)},\n\n  optcrossref = {},\n\n  key = {Planning-Learning},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  cicyt = {congresos},\n\n  year = {2013},\n\n  url = {http://www.cogsys.org/papers/2013poster28.pdf},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {Baltimore (EEUU)},\n\n  optmonth = {},\n\n  pages = {133-147},\n\n  optnote = {Poster},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n OnDroad Planner: Building Tourist Plans using Traveling Social Network Information.\n \n \n \n \n\n\n \n Cenamor, I.; de la Rosa, T.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of Conference on Human Computation & Crowdsourcing (HCOMP'13). Works-in-Progress & Demonstrations, Palm Springs (EEUU), 2013. \n \n\n\n\n
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@inproceedings{hcom13,\n\n  author = {Isabel Cenamor and Tomás de la Rosa and Daniel Borrajo},\n\n  title = {{OnDroad} Planner: Building Tourist Plans using Traveling Social Network Information},\n\n  booktitle = {Proceedings of Conference on Human Computation \\& Crowdsourcing (HCOMP'13). Works-in-Progress \\& Demonstrations},\n\n  optcrossref = {},\n\n  optkey = {},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  url = {hcomp13.pdf},\n\n  year = {2013},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {Palm Springs (EEUU)},\n\n  optmonth = {},\n\n  optpages = {},\n\n  cicyt = {congresos},\n\n  key = {Planning-Learning},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Combining linear programming and automated planning to solve intermodal transportation problems.\n \n \n \n\n\n \n García, J.; Florez, J. E.; Torralba, Á.; Borrajo, D.; Linares-López, C.; García-Olaya, Á.; and Sáenz, J.\n\n\n \n\n\n\n European Journal of Operations Research, 227(1): 216–226. 2013.\n \n\n\n\n
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@article{or-timi,\n\n  author = {Javier García and José E. Florez and Álvaro Torralba and Daniel Borrajo and Carlos Linares-López and Ángel García-Olaya and Juan Sáenz},\n\n  title = {Combining linear programming and automated planning to solve intermodal transportation problems},\n\n  journal = {European Journal of Operations Research},\n\n  year = {2013},\n\n  myurl = {http://dx.doi.org/10.1016/j.ejor.2012.12.018},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  jcr = {Q1, 2013: Operations Research and Management Science, 1.843 (15/79)},\n\n  publisher = {Elsevier},\n\n  volume = {227},\n\n  number = {1},\n\n  optmonth = {},\n\n  pages = {216--226},\n\n  note = {},\n\n  annote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using Activity Recognition for Building Planning Action Models.\n \n \n \n \n\n\n \n Ortiz-Laguna, J.; García-Olaya, Á.; and Borrajo, D.\n\n\n \n\n\n\n International Journal of Distributed Sensor Networks, 2013. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jdsn13,\n\n  author = {Javier Ortiz-Laguna and Ángel García-Olaya and Daniel Borrajo},\n\n  title = {Using Activity Recognition for Building Planning Action Models},\n\n  journal = {International Journal of Distributed Sensor Networks},\n\n  year = {2013},\n\n  publisher = {Hindawi Publishing Corporation},\n\n  key = {Planning-Learning},\n\n  url = {http://dx.doi.org/10.1155/2013/942347},\n\n  volume = {2013},\n\n  number = {},\n\n  month = {},\n\n  pages = {},\n\n  cicyt = {revista},\n\n  jcr = {Q3 2013: Categoría Computer Science, Information Systems: 0.923 (76/135), Categoría Telecommunications:\n\n                  (50/78)},\n\n  optnote = {doi:10.1155/2013/942347},\n\n  optannote = {Special issue: Intelligent Systems in Context-Based Distributed Information Fusion}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Multi-step Generation of Bayesian Networks Models for Software Projects Estimations.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; Linares-López, C.; and Ocón, J.\n\n\n \n\n\n\n The International Journal of Computational Intelligence Systems, 6(5): 796–821. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Multi-step$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 18 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{cci-journal,\n\n  author = {Raquel Fuentetaja and Daniel Borrajo and Carlos Linares-López and Jorge Ocón},\n\n  title = {Multi-step Generation of Bayesian Networks Models for Software Projects Estimations},\n\n  journal = {The International Journal of Computational Intelligence Systems},\n\n  year = {2013},\n\n  publisher = {Taylor \\& Francis},\n\n  key = {Other},\n\n  url = {http://www.tandfonline.com/eprint/sEfCYdXstnZ9gqBfAbFH/full},\n\n  ourl = {http://www.tandfonline.com/doi/abs/10.1080/18756891.2013.805583#.UZXe4isRBDI},\n\n  volume = {6},\n\n  number = {5},\n\n  month = {},\n\n  pages = {796--821},\n\n  cicyt = {revista},\n\n  jcr = {Q4, 2013: 0.451 (108/121), En Categoría Computer Science, Interdisciplinary Applications (96/102)},\n\n  note = {},\n\n  optannote = {DOI: 10.1080/18756891.2013.805583}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Integrating Planning, Execution and Learning to Improve Plan Execution.\n \n \n \n \n\n\n \n Jiménez, S.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n Computational Intelligence Journal, 29(1): 1–36. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Integrating$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{coin,\n\n  author = {Sergio Jiménez and Fernando Fernández and Daniel Borrajo},\n\n  journal = {Computational Intelligence Journal},\n\n  title = {Integrating Planning, Execution and Learning to Improve Plan Execution},\n\n  publisher = {Wiley \\& Blackwell},\n\n  year = {2013},\n\n  key = {Planning-Learning},\n\n  url = {http://onlinelibrary.wiley.com/doi/10.1111/j.1467-8640.2012.00447.x/abstract},\n\n  volume = {29},\n\n  number = {1},\n\n  pages = {1--36},\n\n  cicyt = {revista},\n\n  optnote = {DOI: 10.1111/j.1467-8640.2012.00447.x},\n\n  jcr = {Q3, 2013: 0.87 (78/121)}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Symbolic Merge-and-Shrink for Cost-Optimal Planning.\n \n \n \n \n\n\n \n Torralba, Á.; Linares-López, C.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the IJCAI'13, pages 2394–2400, Beijing (China), 2013. \n \n\n\n\n
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@inproceedings{ijcai13-bdd,\n\n  author = {Álvaro Torralba and Carlos Linares-López and Daniel Borrajo},\n\n  title = {Symbolic Merge-and-Shrink for Cost-Optimal Planning},\n\n  booktitle = {Proceedings of the IJCAI'13},\n\n  optcrossref = {},\n\n  optkey = {},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  url = {http://ijcai.org/papers13/Papers/IJCAI13-352.pdf},\n\n  year = {2013},\n\n  cicyt = {congresos-buenos},\n\n  jcr = {A*},\n\n  key = {Planning-Learning},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {Beijing (China)},\n\n  optmonth = {},\n\n  pages = {2394--2400},\n\n  note = {},\n\n  optannote = {Paper}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Revisiting Regression in Planning.\n \n \n \n \n\n\n \n Alcázar, V.; Borrajo, D.; Fernández, S.; and Fuentetaja, R.\n\n\n \n\n\n\n In Proceedings of the IJCAI'13, pages 2254–2260, Beijing (China), 2013. \n \n\n\n\n
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@inproceedings{ijcai13-fdr,\n\n  author = {Vidal Alcázar and Daniel Borrajo and Susana Fernández and Raquel Fuentetaja},\n\n  title = {Revisiting Regression in Planning},\n\n  booktitle = {Proceedings of the IJCAI'13},\n\n  optcrossref = {},\n\n  optkey = {},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  url = {http://ijcai.org/papers13/Papers/IJCAI13-333.pdf},\n\n  key = {Planning-Learning},\n\n  year = {2013},\n\n  cicyt = {congresos-buenos},\n\n  jcr = {A*},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {Beijing (China)},\n\n  optmonth = {},\n\n  pages = {2254--2260},\n\n  note = {},\n\n  optannote = {Poster}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Learning heuristic functions for cost-based planning.\n \n \n \n \n\n\n \n Virseda, J.; Borrajo, D.; and Alcázar, V.\n\n\n \n\n\n\n In Celorrio, S. J.; Botea, A.; and Karpas, E., editor(s), Preprints of the ICAPS'13 PAL Workshop on Planning and Learning, pages 6–13, Rome (Italy), 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{pal13-heuristic-learning,\n\n  author = {Jesús Virseda and Daniel Borrajo and Vidal Alcázar},\n\n  title = {Learning heuristic functions for cost-based planning},\n\n  booktitle = {Preprints of the ICAPS'13 PAL Workshop on Planning and Learning},\n\n  optcrossref = {},\n\n  optkey = {},\n\n  editor = {Sergio Jiménez Celorrio and Adi Botea and Erez Karpas},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  url = {http://icaps13.icaps-conference.org/wp-content/uploads/2013/05/pal13-proceedings.pdf},\n\n  key = {Planning-Learning},\n\n  year = {2013},\n\n  cicyt = {workshops},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {Rome (Italy)},\n\n  optmonth = {},\n\n  pages = {6--13},\n\n  optnote = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n On the automatic compilation of e-learning models to planning.\n \n \n \n \n\n\n \n Garrido, A.; Onaindía, E.; Morales, L.; Castillo, L.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n The Knowledge Engineering Review, 28(2): 121–136. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"On$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{kereview-adaptaplan,\n\n  author = {Antonio Garrido and Eva Onaindía and Lluvia Morales and Luis Castillo and Susana Fernández and Daniel Borrajo},\n\n  title = {On the automatic compilation of e-learning models to planning},\n\n  journal = {The Knowledge Engineering Review},\n\n  year = {2013},\n\n  url = {http://dx.doi.org/10.1017/S0269888912000380},\n\n  key = {Planning-Learning},\n\n  publisher = {Cambridge University Press},\n\n  volume = {28},\n\n  number = {2},\n\n  optmonth = {},\n\n  pages = {121--136},\n\n  cicyt = {revista},\n\n  jcr = {Q3, 2013: 0.957 (74/121)},\n\n  optjcr = {2004: 1.237 (28/78), 2005: 2.179 (16/79), 2006: 0.930 (43/85), 2007: 1.312 (35/93)},\n\n  note = {},\n\n  optannote = {ISSN: 0269-8889, http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=8833585&fulltextType=RV&fileId=S0269888912000380}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using Automated Planning for Improving Data Mining Processes.\n \n \n \n \n\n\n \n Fernández, S.; de la Rosa, T.; Fernández, F.; Suárez, R.; Ortiz, J.; Borrajo, D.; and Manzano, D.\n\n\n \n\n\n\n The Knowledge Engineering Review, 28(2): 157-173. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{kereview-aukb,\n\n  author = {Susana Fernández and Tomás de la Rosa and Fernando Fernández and Rubén Suárez and Javier Ortiz and\n\n                  Daniel Borrajo and David Manzano},\n\n  title = {Using Automated Planning for Improving Data Mining Processes},\n\n  journal = {The Knowledge Engineering Review},\n\n  year = {2013},\n\n  url = {http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=8830100&fulltextType=RV&fileId=S0269888912000409},\n\n  key = {Planning-Learning},\n\n  publisher = {Cambridge University Press},\n\n  volume = {28},\n\n  number = {2},\n\n  optmonth = {},\n\n  pages = {157-173},\n\n  cicyt = {revista},\n\n  jcr = {Q3, 2013: 0.957 (74/121)},\n\n  optjcr = {2004: 1.237 (28/78), 2005: 2.179 (16/79), 2006: 0.930 (43/85), 2007: 1.312 (35/93)},\n\n  note = {},\n\n  optannote = {ISSN: 0269-8889}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Case-Based Approach to Heuristic Planning.\n \n \n \n \n\n\n \n de la Rosa, T.; García-Olaya, A.; and Borrajo, D.\n\n\n \n\n\n\n Applied Intelligence, 39(1): 184–201. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{applied-intelligence-cbr,\n\n  author = {Tomás de la Rosa and Angel García-Olaya and Daniel Borrajo},\n\n  journal = {Applied Intelligence},\n\n  title = {A Case-Based Approach to Heuristic Planning},\n\n  publisher = {Springer Verlag},\n\n  year = {2013},\n\n  key = {Planning-Learning},\n\n  url = {applied13.pdf},\n\n  editor = {},\n\n  volume = {39},\n\n  number = {1},\n\n  pages = {184--201},\n\n  doi = {10.1007/s10489-012-0404-6},\n\n  cicyt = {revista},\n\n  note = {},\n\n  optannote = {http://link.springer.com/article/10.1007\\%2Fs10489-012-0404-6. ISBN: 0924-669X, ISBN online: 1573-7497},\n\n  jcr = {2012: 1.853 (32/115)}\n\n}\n\n\n\n

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\n \n 2012\n \n \n (23)\n \n \n

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\n \n\n \n \n \n \n \n Proceedings of the Fifth Annual Symposium on Combinatorial Search, SOCS 2012.\n \n \n \n\n\n \n Borrajo, D.; Felner, A.; Korf, R.; Likhachev, M.; Linares López, C.; Ruml, W.; and Sturtevant, N.,\n editors.\n \n\n\n \n\n\n\n Niagara Falls, Ontario (Canada), July 2012.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@Proceedings{\t  borrajo.d.felner.a.ea:proceedings,\n  title\t\t= {Proceedings of the Fifth Annual Symposium on Combinatorial\n\t\t  Search, SOCS 2012},\n  year\t\t= 2012,\n  editor\t= {Daniel Borrajo and Ariel Felner and Richard Korf and Maxim\n\t\t  Likhachev and Carlos {Linares L\\'opez} and Wheeler Ruml and\n\t\t  Nathan Sturtevant},\n  address\t= {Niagara Falls, Ontario (Canada)},\n  month\t\t= jul\n}\n\n

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\n \n\n \n \n \n \n \n \n The Symposium on Combinatorial Search.\n \n \n \n \n\n\n \n Borrajo, D.; Likhachev, M.; and Linares López, C.\n\n\n \n\n\n\n AI Communications, 25(3): 209–210. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@Article{\t  borrajo.d.likhachev.m.ea:symposium,\n  author\t= {Daniel Borrajo and Maxim Likhachev and Carlos {Linares\n\t\t  L\\'opez}},\n  title\t\t= {The Symposium on Combinatorial Search},\n  journal\t= {AI Communications},\n  year\t\t= 2012,\n  volume\t= 25,\n  number\t= 3,\n  pages\t\t= {209--210},\n  doi\t\t= {10.3233/AIC-2012-0530},\n  url\t\t= {http://iospress.metapress.com/content/9u44m4134p1u4l76/}\n}\n\n

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\n \n\n \n \n \n \n \n \n A Survey of the Seventh International Planning Competition.\n \n \n \n \n\n\n \n Coles, A. J.; Coles, A.; García Olaya, A.; Jiménez, S.; Linares López, C.; Sanner, S.; and Yoon, S.\n\n\n \n\n\n\n AI Magazine, 33(1): 83–88. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@Article{\t  coles.aj.coles.a.ea:survey,\n  author\t= {Amanda Jane Coles and Andrew Coles and Angel {Garc\\'ia\n\t\t  Olaya} and Sergio Jim\\'enez and Carlos {Linares L\\'opez}\n\t\t  and Scott Sanner and Sungwook Yoon},\n  title\t\t= {A Survey of the Seventh International Planning\n\t\t  Competition},\n  journal\t= {{AI} Magazine},\n  year\t\t= {2012},\n  volume\t= {33},\n  number\t= {1},\n  pages\t\t= {83--88},\n  url\t\t= {http://www.aaai.org/ojs/index.php/aimagazine/issue/view/197/showToc}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Precomputed-direction Heuristics for Suboptimal Grid-based Path-finding.\n \n \n \n \n\n\n \n Parra, Á.; Torralba, Á.; and Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Fifth Annual Symposium on Combinatorial Search, SOCS 2012, pages 211–212, Niagara Falls, Ontario (Canada), July 2012. \n \n\n\n\n
\n\n\n\n \n \n $\"Precomputed-direction$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  parra.torralba.ea:precomputed-direction,\n  author\t= {Álvaro Parra and Álvaro Torralba and Carlos {Linares\n\t\t  L\\'opez}},\n  title\t\t= {Precomputed-direction Heuristics for Suboptimal Grid-based\n\t\t  Path-finding},\n  booktitle\t= {Proceedings of the Fifth Annual Symposium on Combinatorial\n\t\t  Search, SOCS 2012},\n  pages\t\t= {211--212},\n  year\t\t= 2012,\n  address\t= {Niagara Falls, Ontario (Canada)},\n  month\t\t= jul,\n  url\t\t= {http://www.aaai.org/Library/SOCS/socs12contents.php}\n}\n\n

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\n \n\n \n \n \n \n \n Calibrating a motion model based on reinforcement learning for pedestrian simulation.\n \n \n \n\n\n \n Martinez-Gil, F.; Lozano, M.; and Fernández, F.\n\n\n \n\n\n\n Volume 7660 LNCS 2012.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

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@book{Martinez-Gil2012,\nabstract = {In this paper, the calibration of a framework based in Multi-agent Reinforcement Learning (RL) for generating motion simulations of pedestrian groups is presented. The framework sets a group of autonomous embodied agents that learn to control individually its instant velocity vector in scenarios with collisions and friction forces. The result of the process is a different learned motion controller for each agent. The calibration of both, the physical properties involved in the motion of our embodied agents and the corresponding dynamics, is an important issue for a realistic simulation. The physics engine used has been calibrated with values taken from real pedestrian dynamics. Two experiments have been carried out for testing this approach. The results of the experiments are compared with databases of real pedestrians in similar scenarios. As a comparison tool, the diagram of speed versus density, known as fundamental diagram in the literature, is used. {\\textcopyright} 2012 Springer-Verlag Berlin Heidelberg.},\nauthor = {Martinez-Gil, F. and Lozano, M. and Fern{\\'{a}}ndez, F.},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\nisbn = {9783642347092},\nissn = {03029743},\nkeywords = {Pedestrian motion learning,Reinforcement Learning},\ntitle = {{Calibrating a motion model based on reinforcement learning for pedestrian simulation}},\nvolume = {7660 LNCS},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n Reinforcement learning for decision-making in a business simulator.\n \n \n \n\n\n \n GarcΊa, J.; Borrajo, F.; and FernÁndez, F.\n\n\n \n\n\n\n International Journal of Information Technology and Decision Making, 11(5). 2012.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{GarcIa2012,\nabstract = {Business simulators are powerful tools for both supporting the decision-making process of business managers as well as for business education. An example is SIMBA (SIMulator for Business Administration), a powerful simulator which is currently used as a web-based platform for business education in different institutions. In this paper, we propose the application of reinforcement learning (RL) for the creation of intelligent agents that can manage virtual companies in SIMBA. This application is not trivial, given the particular intrinsic characteristics of SIMBA: it is a generalized domain where hundreds of parameters modify the domain behavior; it is a multi-agent domain where both cooperation and competition among different agents can coexist; it is required to set dozens of continuous decision variables for a given business decision, which is made only after the study of hundreds of continuous variables. We will demonstrate empirically that all these challenges can be overcome through the use of RL, showing results for different learning scenarios. {\\textcopyright} 2012 World Scientific Publishing Company.},\nauthor = {Garc{\\'{I}}a, J. and Borrajo, F. and Fern{\\'{A}}ndez, F.},\ndoi = {10.1142/S0219622012500277},\nissn = {02196220},\njournal = {International Journal of Information Technology and Decision Making},\nkeywords = {Reinforcement learning,business simulator,competitive learning,multi-agent learning},\nnumber = {5},\ntitle = {{Reinforcement learning for decision-making in a business simulator}},\nvolume = {11},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n \n A review of machine learning for automated planning.\n \n \n \n \n\n\n \n Jiménez, S.; De La Rosa, T.; Fernández, S.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n The Knowledge Engineering Review, 27(04): 433–467. dec 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Jimenez2012,\nabstract = {Recent discoveries in automated planning are broadening the scope of planners, from toy problems to real applications. However, applying automated planners to real-world problems is far from simple. On the one hand, the definition of accurate action models for planning is still a bottleneck. On the other hand, off-the-shelf planners fail to scale-up and to provide good solutions in many domains. In these problematic domains, planners can exploit domain-specific control knowledge to improve their performance in terms of both speed and quality of the solutions. However, manual definition of control knowledge is quite difficult. This paper reviews recent techniques in machine learning for the automatic definition of planning knowledge. It has been organized according to the target of the learning process: automatic definition of planning action models and automatic definition of planning control knowledge. In addition, the paper reviews the advances in the related field of reinforcement learning. {\\textcopyright} 2012 Cambridge University Press.},\nauthor = {Jim{\\'{e}}nez, Sergio and {De La Rosa}, Tom{\\'{a}}s and Fern{\\'{a}}ndez, Susana and Fern{\\'{a}}ndez, Fernando and Borrajo, Daniel},\ndoi = {10.1017/S026988891200001X},\nfile = {:home/fernando/papers/tmp/review{\\_}of{\\_}machine{\\_}learning{\\_}for{\\_}automated{\\_}planning.pdf:pdf},\nissn = {0269-8889},\njournal = {The Knowledge Engineering Review},\nmonth = {dec},\nnumber = {04},\npages = {433--467},\ntitle = {{A review of machine learning for automated planning}},\nurl = {http://www.journals.cambridge.org/abstract{\\_}S026988891200001X},\nvolume = {27},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n \n Multi-agent Reinforcement Learning for Simulating Pedestrian Navigation.\n \n \n \n \n\n\n \n Martinez-Gil, F.; Lozano, M.; and Fern?ndez, F.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 7113 LNAI, pages 54–69. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Multi-agent$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{Martinez-Gil2012a,\nabstract = {In this paper we introduce a Multi-agent system that uses Reinforcement Learning (RL) techniques to learn local navigational behaviors to simulate virtual pedestrian groups. The aim of the paper is to study empirically the validity of RL to learn agent-based navigation controllers and their transfer capabilities when they are used in simulation environments with a higher number of agents than in the learned scenario. Two RL algorithms which use Vector Quantization (VQ) as the generalization method for the space state are presented. Both strategies are focused on obtaining a good vector quantizier that generalizes adequately the state space of the agents. We empirically state the convergence of both methods in our navigational Multi-agent learning domain. Besides, we use validation tools of pedestrian models to analyze the simulation results in the context of pedestrian dynamics. The simulations carried out, scaling up the number of agents in our environment (a closed room with a door through which the agents have to leave), have revealed that the basic characteristics of pedestrian movements have been learned. {\\textcopyright} 2012 Springer-Verlag Berlin Heidelberg.},\nauthor = {Martinez-Gil, Francisco and Lozano, Miguel and Fern?ndez, Fernando},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\ndoi = {10.1007/978-3-642-28499-1_4},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F978-3-642-28499-1{\\_}4.pdf:pdf},\nisbn = {9783642284984},\nissn = {03029743},\npages = {54--69},\ntitle = {{Multi-agent Reinforcement Learning for Simulating Pedestrian Navigation}},\nurl = {http://link.springer.com/10.1007/978-3-642-28499-1{\\_}4},\nvolume = {7113 LNAI},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n \n A META-TOOL TO SUPPORT THE DEVELOPMENT OF KNOWLEDGE ENGINEERING METHODOLOGIES AND PROJECTS.\n \n \n \n \n\n\n \n FLÓREZ, J. E.; CARBÓ, J.; and FERNÁNDEZ, F.\n\n\n \n\n\n\n International Journal of Software Engineering and Knowledge Engineering, 22(08): 1055–1083. dec 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{FLOREZ2012,\nabstract = {Knowledge-based systems (KBSs) or expert systems (ESs) are able to solve problems generally through the application of knowledge representing a domain and a set of inference rules. In knowledge engineering (KE), the use of KBSs in the real world, three principal disadvantages have been encountered. First, the knowledge acquisition process has a very high cost in terms of money and time. Second, processing information provided by experts is often difficult and tedious. Third, the establishment of mark times associated with each project phase is difficult due to the complexity described in the previous two points. In response to these obstacles, many methodologies have been developed, most of which include a tool to support the application of the given methodology. Nevertheless, there are advantages and disadvantages inherent in KE methodologies, as well. For instance, particular phases or components of certain methodologies seem to be better equipped than others to respond to a given problem. However, since KE tools currently available support just one methodology the joint use of these phases or components from different methodologies for the solution of a particular problem is hindered. This paper presents KEManager, a generic meta-tool that facilitates the definition and combined application of phases or components from different methodologies. Although other methodologies could be defined and combined in the KEManager, this paper focuses on the combination of two well-known KE methodologies, CommonKADS and IDEAL, together with the most commonly-applied knowledge acquisition methods. The result is an example of the ad hoc creation of a new methodology from pre-existing methodologies, allowing for the adaptation of the KE process to an organization or domain-specific characteristics. The tool was evaluated by students at Carlos III University of Madrid (Spain). {\\textcopyright} 2012 World Scientific Publishing Company.},\nauthor = {FL{\\'{O}}REZ, JOS{\\'{E}} ELOY and CARB{\\'{O}}, JAVIER and FERN{\\'{A}}NDEZ, FERNANDO},\ndoi = {10.1142/S0218194012500283},\nfile = {:home/fernando/papers/tmp/s0218194012500283.pdf:pdf},\nissn = {0218-1940},\njournal = {International Journal of Software Engineering and Knowledge Engineering},\nkeywords = {CommonKADS,IDEAL,Knowledge engineering,expert systems,knowledge-based systems,software tools},\nmonth = {dec},\nnumber = {08},\npages = {1055--1083},\ntitle = {{A META-TOOL TO SUPPORT THE DEVELOPMENT OF KNOWLEDGE ENGINEERING METHODOLOGIES AND PROJECTS}},\nurl = {http://www.worldscientific.com/doi/abs/10.1142/S0218194012500283},\nvolume = {22},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n \n A kinodynamic planning-learning algorithm for complex robot motor control.\n \n \n \n \n\n\n \n Gonzalez-Quijano, J.; Abderrahim, M.; Fernandez, F.; and Bensalah, C.\n\n\n \n\n\n\n In 2012 IEEE Conference on Evolving and Adaptive Intelligent Systems, pages 80–83, may 2012. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Gonzalez-Quijano2012,\nabstract = {Robot motor control learning is currently one of the most active research areas in robotics. Many learning techniques have been developed for relatively simple problems. However, very few of them have direct applicability in complex robotic systems without assuming prior knowledge about the task, mainly due to three facts. Firstly, they scale badly to continues and high dimensional problems. Secondly, they need too many real robot-environment interactions. Finally, they are not capable of adapting to environment or robot dynamic changes. In order to overcome these problems, we have developed a new algorithm capable of finding from scratch open-loop state-action trajectory solutions by mixing sample-based tree kinodynamic planning with dynamic model learning. Some results demonstrating the viability of this new type of approach in the cart-pole swing-up task problem are presented. {\\textcopyright} 2012 IEEE.},\nauthor = {Gonzalez-Quijano, Javier and Abderrahim, Mohamed and Fernandez, Fernando and Bensalah, Choukri},\nbooktitle = {2012 IEEE Conference on Evolving and Adaptive Intelligent Systems},\ndoi = {10.1109/EAIS.2012.6232809},\nfile = {:home/fernando/papers/tmp/06232809.pdf:pdf},\nisbn = {978-1-4673-1727-6},\nmonth = {may},\npages = {80--83},\npublisher = {IEEE},\ntitle = {{A kinodynamic planning-learning algorithm for complex robot motor control}},\nurl = {http://ieeexplore.ieee.org/document/6232809/},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n \n Calibrating a Motion Model Based on Reinforcement Learning for Pedestrian Simulation.\n \n \n \n \n\n\n \n Martinez-Gil, F.; Lozano, M.; and Fern?ndez, F.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 7660 LNCS, pages 302–313. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Calibrating$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

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@incollection{Martinez-Gil2012b,\nabstract = {In this paper, the calibration of a framework based in Multi-agent Reinforcement Learning (RL) for generating motion simulations of pedestrian groups is presented. The framework sets a group of autonomous embodied agents that learn to control individually its instant velocity vector in scenarios with collisions and friction forces. The result of the process is a different learned motion controller for each agent. The calibration of both, the physical properties involved in the motion of our embodied agents and the corresponding dynamics, is an important issue for a realistic simulation. The physics engine used has been calibrated with values taken from real pedestrian dynamics. Two experiments have been carried out for testing this approach. The results of the experiments are compared with databases of real pedestrians in similar scenarios. As a comparison tool, the diagram of speed versus density, known as fundamental diagram in the literature, is used. {\\textcopyright} 2012 Springer-Verlag Berlin Heidelberg.},\nauthor = {Martinez-Gil, Francisco and Lozano, Miguel and Fern?ndez, Fernando},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\ndoi = {10.1007/978-3-642-34710-8_28},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F978-3-642-34710-8{\\_}28.pdf:pdf},\nisbn = {9783642347092},\nissn = {03029743},\nkeywords = {Pedestrian motion learning,Reinforcement Learning},\npages = {302--313},\ntitle = {{Calibrating a Motion Model Based on Reinforcement Learning for Pedestrian Simulation}},\nurl = {http://link.springer.com/10.1007/978-3-642-34710-8{\\_}28},\nvolume = {7660 LNCS},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n \n A prototype-based method for classification with time constraints: a case study on automated planning.\n \n \n \n \n\n\n \n García-Durán, R.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n Pattern Analysis and Applications, 15(3): 261–277. aug 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Garcia-Duran2012,\nabstract = {The main goal of Nearest Prototype Classification is to reduce storage space and retrieval time of classical Instance-Based Learning (IBL) algorithms. This motivation is higher in relational data since relational distance metrics are much more expensive to compute than classical distances like Euclidean distance. In this paper, we present an algorithm to build Relational Nearest Prototype Classifiers (RNPCs). When compared with Relational Instance-Based Learning (Relational IBL or RIBL) approaches, the algorithm is able to dramatically reduce the number of instances by selecting the most relevant prototypes, maintaining similar accuracy. The number of prototypes is obtained automatically by the algorithm, although it can also be bound by the user. In this work, we also show an application of RNPC for automated planning. Specifically, we describe a modeling task where a relational policy is built following an IBL approach. This approach uses the decisions taken by a planning system as learning examples. We show that when the number of learning examples is reduced with RNPC, the resulting policy is able to scale up better than the original planning system. {\\textcopyright} 2010 Springer-Verlag London Limited.},\nauthor = {Garc{\\'{i}}a-Dur{\\'{a}}n, Roc{\\'{i}}o and Fern{\\'{a}}ndez, Fernando and Borrajo, Daniel},\ndoi = {10.1007/s10044-010-0194-6},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2Fs10044-010-0194-6.pdf:pdf},\nissn = {1433-7541},\njournal = {Pattern Analysis and Applications},\nkeywords = {Automated planning,Nearest prototype classification,Relational instance-based learning,Relational learning},\nmonth = {aug},\nnumber = {3},\npages = {261--277},\ntitle = {{A prototype-based method for classification with time constraints: a case study on automated planning}},\nurl = {http://link.springer.com/10.1007/s10044-010-0194-6},\nvolume = {15},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n \n Safe exploration of state and action spaces in reinforcement learning.\n \n \n \n \n\n\n \n Garcia, J.; and Fernández, F.\n\n\n \n\n\n\n Journal of Artificial Intelligence Research, 45. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Safe$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Garcia2012,\nabstract = {In this paper, we consider the important problem of safe exploration in reinforcement learning. While reinforcement learning is well-suited to domains with complex transition dynamics and high-dimensional state-action spaces, an additional challenge is posed by the need for safe and efficient exploration. Traditional exploration techniques are not particularly useful for solving dangerous tasks, where the trial and error process may lead to the selection of actions whose execution in some states may result in damage to the learning system (or any other system). Consequently, when an agent begins an interaction with a dangerous and high-dimensional state-action space, an important question arises; namely, that of how to avoid (or at least minimize) damage caused by the exploration of the state-action space. We introduce the PI-SRL algorithm which safely improves suboptimal albeit robust behaviors for continuous state and action control tasks and which efficiently learns from the experience gained from the environment. We evaluate the proposed method in four complex tasks: automatic car parking, pole-balancing, helicopter hovering, and business management. {\\textcopyright} 2012 AI Access Foundation.},\nauthor = {Garcia, J. and Fern{\\'{a}}ndez, Fernando},\ndoi = {10.1613/jair.3761},\nfile = {:home/fernando/papers/tmp/live-3761-6687-jair.pdf:pdf},\nissn = {10769757},\njournal = {Journal of Artificial Intelligence Research},\ntitle = {{Safe exploration of state and action spaces in reinforcement learning}},\nurl = {http://jair.org/papers/paper3761.html},\nvolume = {45},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n \n An Online Utility-Based Approach for Sampling Dynamic Ocean Fields.\n \n \n \n \n\n\n \n Garcia-Olaya, A.; Py, F.; Das, J.; and Rajan, K.\n\n\n \n\n\n\n IEEE Journal of Oceanic Engineering, 37(2): 185–203. apr 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"An$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Garcia-Olaya2012,\nabstract = {The coastal ocean is a dynamic and complex environment due to the confluence of atmospheric, oceanographic, estuarine/riverine, and land-sea interactions. Yet it continues to be undersampled, resulting in poor understanding of dynamic, episodic, and complex phenomena such as harmful algal blooms, anoxic zones, coastal plumes, thin layers, and frontal zones. Often these phenomena have no viable biological or computational models that can provide guidance for sampling. Returning targeted water samples for analysis becomes critical for biologists to assimilate data for model synthesis. In our work, the scientific emphasis on building a species distribution model necessitates spatially distributed sample collection from within hotspots in a large volume of a dynamic field of interest. To do so, we propose an autonomous approach to sample acquisition based on an online calculation of sample utility. A series of reward functions provide a balance between temporal and spatial scales of oceanographic sampling and do so in such a way that science preferences or evolving knowledge about the feature of interest can be incorporated in the decision process. This utility calculation is undertaken onboard a powered autonomous underwater vehicle (AUV) with specialized water samplers for the upper water column. For validation, we provide experimental results using archival AUV data along with an at-sea demonstration in Monterey Bay, CA.},\nauthor = {Garcia-Olaya, Angel and Py, Fr{\\'{e}}d{\\'{e}}ric and Das, Jnaneshwar and Rajan, Kanna},\ndoi = {10.1109/JOE.2012.2183934},\nisbn = {0364-9059},\nissn = {0364-9059},\njournal = {IEEE Journal of Oceanic Engineering},\nmendeley-groups = {Papers/2018-OSP},\nmonth = {apr},\nnumber = {2},\npages = {185--203},\ntitle = {{An Online Utility-Based Approach for Sampling Dynamic Ocean Fields}},\nurl = {http://ieeexplore.ieee.org/document/6168799/},\nvolume = {37},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n \n A Survey of the Seventh International Planning Competition.\n \n \n \n \n\n\n \n Coles, A.; Coles, A.; García-Olaya, A.; Jiménez, S.; Linares López, C.; Sanner, S.; and Yoon, S.\n\n\n \n\n\n\n AI Magazine, 33(1): 83–88. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aim12,\nabstract = {In this article we review the 2011 Interna- tional Planning Competition. We give an overview of the history of the competition, dis- cussing how it has developed since its first edi- tion in 1998. The 2011 competition was run in three main separate tracks: the deterministic (classical) track; the learning track; and the uncertainty track. Each track proposed its own distinct set of new challenges and the partici- pants rose to these admirably, the results of each track showing promising progress in each area. The competition attracted a record num- ber of participants this year, showing its con- tinued and strong position as a major central pillar of the international planning research community.},\nauthor = {Coles, Amanda and Coles, Andrew and Garc{\\'{i}}a-Olaya, Angel and Jim{\\'{e}}nez, Sergio and {Linares L{\\'{o}}pez}, Carlos and Sanner, Scott and Yoon, Sungwook},\ndoi = {10.1609/aimag.v33i1.2392},\nfile = {:C$\\backslash$:/Users/angel/Documents/Mendeley Desktop/Coles et al. - 2012 - A Survey of the Seventh International Planning Competition.pdf:pdf},\nissn = {07384602},\njournal = {AI Magazine},\nmendeley-groups = {Papers/2018-OSP},\nnumber = {1},\npages = {83--88},\ntitle = {{A Survey of the Seventh International Planning Competition}},\nurl = {http://www.aaai.org/ojs/index.php/aimagazine/issue/view/197/showToc http://www.aaai.org/ojs/index.php/aimagazine/article/view/2392 http://www.scopus.com/inward/record.url?eid=2-s2.0-84861350540{\\&}partnerID=MN8TOARS},\nvolume = {33},\nyear = {2012}\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Review of Machine Learning for Automated Planning.\n \n \n \n \n\n\n \n Jiménez, S.; de la Rosa, T.; Fernández, S.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n The Knowledge Engineering Review, 27(4): 433–467. December 2012.\n \n\n\n\n
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@article{kereview-ml,\n\n  author = {Sergio Jiménez and Tomás de la Rosa and Susana Fernández and Fernando Fernández and Daniel Borrajo},\n\n  journal = {The Knowledge Engineering Review},\n\n  title = {A Review of Machine Learning for Automated Planning},\n\n  publisher = {Cambridge University Press},\n\n  year = {2012},\n\n  key = {Planning-Learning},\n\n  url = {http://dx.doi.org/10.1017/S026988891200001X},\n\n  editor = {},\n\n  volume = {27},\n\n  number = {4},\n\n  series = {},\n\n  address = {},\n\n  month = {December},\n\n  pages = {433--467},\n\n  cicyt = {revista},\n\n  note = {},\n\n  jcr = {Q4, 2012: 0.590 (91/115)},\n\n  optjcr = {2004: 1.237 (28/78), 2005: 2.179 (16/79), 2006: 0.930 (43/85), 2007: 1.312 (35/93)},\n\n  optannote = {ISSN: 0269-8889}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Prototype-Based Method for Classification with Time Constraints: A Case Study on Automated Planning.\n \n \n \n \n\n\n \n García-Durán, R.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n Pattern Analysis and Applications Journal, 15(3): 261–277. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{paa12,\n\n  author = {Rocío García-Durán and Fernando Fernández and Daniel Borrajo},\n\n  title = {A Prototype-Based Method for Classification with Time Constraints: A Case Study on Automated Planning},\n\n  journal = {Pattern Analysis and Applications Journal},\n\n  year = {2012},\n\n  url = {http://dx.doi.org/10.1007/s10044-010-0194-6},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  publisher = {Springer},\n\n  jcr = {Q3, 2012: 0.814 (78/115)},\n\n  volume = {15},\n\n  number = {3},\n\n  month = {},\n\n  pages = {261--277},\n\n  note = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Performance analysis of planning portfolios.\n \n \n \n \n\n\n \n Núñez, S.; Borrajo, D.; and Linares-López, C.\n\n\n \n\n\n\n In , editor(s), Proceedings of the Fifth International Symposium on Combinatorial Search (SoCS-2012), Niagara (Canada), 2012. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Performance$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{socs12-portfolios,\n\n  author = {Sergio Núñez and Daniel Borrajo and Carlos Linares-López},\n\n  booktitle = {Proceedings of the Fifth International Symposium on Combinatorial Search (SoCS-2012)},\n\n  title = {Performance analysis of planning portfolios},\n\n  publisher = {AAAI Press},\n\n  year = {2012},\n\n  key = {Planning-Learning},\n\n  url = {http://www.aaai.org/Library/SOCS/socs12contents.php},\n\n  editor = {},\n\n  address = {Niagara (Canada)},\n\n  pages = {},\n\n  cicyt = {congresos},\n\n  jcr = {},\n\n  note = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Probabilistically Reusing Plans in Deterministic Planning.\n \n \n \n\n\n \n Borrajo, D.; and Veloso, M.\n\n\n \n\n\n\n In , editor(s), Proceedings of ICAPS'12 workshop on Heuristics and Search for Domain-Independent Planning, pages 17-25, Atibaia (Brazil), 2012. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{workshop-icaps12-errtplan,\n\n  author = {Daniel Borrajo and Manuela Veloso},\n\n  booktitle = {Proceedings of ICAPS'12 workshop on Heuristics and Search for Domain-Independent Planning},\n\n  title = {Probabilistically Reusing Plans in Deterministic Planning},\n\n  publisher = {},\n\n  year = {2012},\n\n  key = {Planning-Learning},\n\n  myurl = {http://icaps12.icaps-conference.org/workshops/hsdip2012-proceedings.pdf},\n\n  editor = {},\n\n  volume = {},\n\n  series = {},\n\n  address = {Atibaia (Brazil)},\n\n  month = {},\n\n  pages = {17-25},\n\n  cicyt = {workshops},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n PELEA: a Domain-Independent Architecture for Planning, Execution and Learning.\n \n \n \n \n\n\n \n Guzmán, C.; Alcázar, V.; Prior, D.; Onaindía, E.; Borrajo, D.; Fdez-Olivares, J.; and Quintero, E.\n\n\n \n\n\n\n In , editor(s), Proceedings of ICAPS'12 Scheduling and Planning Applications woRKshop (SPARK), pages 38-45, Atibaia (Brazil), 2012. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"PELEA:$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 8 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{spark12,\n\n  author = {César Guzmán and Vidal Alcázar and David Prior and Eva Onaindía and Daniel Borrajo and Juan Fdez-Olivares and Ezequiel Quintero},\n\n  booktitle = {Proceedings of ICAPS'12 Scheduling and Planning Applications woRKshop (SPARK)},\n\n  title = {{PELEA}: a Domain-Independent Architecture for Planning, Execution and Learning},\n\n  publisher = {AAAI Press},\n\n  year = {2012},\n\n  key = {Planning-Learning},\n\n  url = {spark12.pdf},\n\n  editor = {},\n\n  volume = {},\n\n  series = {},\n\n  address = {Atibaia (Brazil)},\n\n  month = {},\n\n  pages = {38-45},\n\n  cicyt = {workshops},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Variable resolution planning through predicate relaxation.\n \n \n \n \n\n\n \n Martínez, M.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In , editor(s), Proceedings of ICAPS'12 workshop on Planning and Plan Execution for Real-World Systems: Principles and Practices (PlanEx), pages 5–12, Atibaia (Brazil), 2012. \n \n\n\n\n
\n\n\n\n \n \n $\"Variable$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{planex2012,\n\n  author = {Moisés Martínez and Fernando Fernández and Daniel Borrajo},\n\n  booktitle = {Proceedings of ICAPS'12 workshop on Planning and Plan Execution for Real-World Systems: Principles and Practices (PlanEx)},\n\n  title = {Variable resolution planning through predicate relaxation},\n\n  publisher = {},\n\n  year = {2012},\n\n  key = {Planning-Learning},\n\n  url = {planex2012.pdf},\n\n  editor = {},\n\n  volume = {},\n\n  series = {},\n\n  address = {Atibaia (Brazil)},\n\n  month = {},\n\n  pages = {5--12},\n\n  cicyt = {workshops},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Modeling Motivations, Personality Traits and Emotional States in Deliberative Agents Based on Automated Planning.\n \n \n \n \n\n\n \n Pérez, D.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Filipe, J.; and Fred, A., editor(s), 3rd International Conference on Agents and Artificial Intelligence (ICAART 2011), volume CCIS 271, of Lecture Notes on Communications in Computer and Information Science, pages 146–160, Heidelberg, 2012. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Modeling$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icaart12-ln,\n\n  author = {Daniel Pérez and Susana Fernández and Daniel Borrajo},\n\n  title = {Modeling Motivations, Personality Traits and Emotional States in Deliberative Agents Based on Automated Planning},\n\n  booktitle = {3rd International Conference on Agents and Artificial Intelligence (ICAART 2011)},\n\n  optcrossref = {},\n\n  publisher = {Springer Verlag},\n\n  series = {Lecture Notes on Communications in Computer and Information Science},\n\n  key = {Planning-Learning},\n\n  editor = {J. Filipe and A. Fred},\n\n  volume = {CCIS 271},\n\n  optnumber = {},\n\n  url = {icaart12-ln.pdf},\n\n  year = {2012},\n\n  cicyt = {lncs},\n\n  organization = {},\n\n  address = {Heidelberg},\n\n  month = {},\n\n  pages = {146--160},\n\n  note = {},\n\n  optannote = {},\n\n  jcr = {C}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using Linear Programming to solve Clustered Oversubscription Planning Problems for Designing e-Courses.\n \n \n \n \n\n\n \n Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n Expert Systems with Applications, 39(5): 5178–5188. April 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{expertsystems12,\n\n  author = {Susana Fernández and Daniel Borrajo},\n\n  title = {Using Linear Programming to solve Clustered Oversubscription Planning Problems for Designing e-Courses},\n\n  journal = {Expert Systems with Applications},\n\n  year = {2012},\n\n  publisher = {Elsevier},\n\n  key = {Planning-Learning},\n\n  url = {http://dx.doi.org/10.1016/j.eswa.2011.11.021},\n\n  volume = {39},\n\n  number = {5},\n\n  month = {April},\n\n  pages = {5178--5188},\n\n  cicyt = {revista},\n\n  jcr = {Q1, 2012: 1.854 (31/115) En Categoría Engineering, Electrical \\& Electronic 56/243, En Categoría\n\n                  Operations Research \\& Management Science 13/79},\n\n  optjcr = {2004: 1.247 (26/78), 2005: 1.236 (32/79), 2006: 0.957 (41/85), 2007: 1.177 (40/93), 2008: 2.596 (17/94), En Categoría Operations Research \\& Management Science:\n\n                  2007 (11/60), 2008 (1/64)},\n\n  note = {},\n\n  optannote = {ISSN: 0957-4174}\n\n}\n\n\n\n

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\n \n 2011\n \n \n (21)\n \n \n

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\n \n\n \n \n \n \n \n Proceedings of the Fourth Annual Symposium on Combinatorial Search, SOCS 2011.\n \n \n \n\n\n \n Borrajo, D.; Likhachev, M.; and Linares López, C.,\n editors.\n \n\n\n \n\n\n\n Cardona (Barcelona), July 2011.\n \n\n\n\n
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@Proceedings{\t  borrajo.d.likhachev.m.ea:proceedings,\n  title\t\t= {Proceedings of the Fourth Annual Symposium on\n\t\t  Combinatorial Search, SOCS 2011},\n  year\t\t= 2011,\n  editor\t= {Daniel Borrajo and Maxim Likhachev and Carlos {Linares\n\t\t  L\\'opez}},\n  address\t= {Cardona (Barcelona)},\n  month\t\t= jul\n}\n\n

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\n \n\n \n \n \n \n \n Planning Multi-Modal Transportation Problems.\n \n \n \n\n\n \n E.~Flórez, J.; Torralba, Á.; García, J.; Linares López, C.; García Olaya, A.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the Twenty-first International Conference on Automated Planning and Scheduling (ICAPS'11), pages 66–73, Freiburg (Germany), June 2011. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  florez.je.torralba.ea:planning,\n  author\t= {Jos\\'e E.~Fl\\'orez and Álvaro Torralba and Javier García\n\t\t  and Carlos {Linares L\\'opez} and Angel {García Olaya} and\n\t\t  Daniel Borrajo},\n  title\t\t= {Planning Multi-Modal Transportation Problems},\n  booktitle\t= {Proceedings of the Twenty-first International Conference\n\t\t  on Automated Planning and Scheduling (ICAPS'11)},\n  pages\t\t= {66--73},\n  year\t\t= {2011},\n  address\t= {Freiburg (Germany)},\n  month\t\t= jun\n}\n\n

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\n \n\n \n \n \n \n \n The 2011 International Planning Competition.\n \n \n \n\n\n \n García-Olaya, Á.; Jiménez, S.; and Linares López, C.\n\n\n \n\n\n\n Technical Report Universidad Carlos III de Madrid, Madrid, Spain, July 2011.\n http://hdl.handle.net/10016/11710\n\n\n\n
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@TechReport{\t  garcia-olaya.a.jimenez.s.ea:2011,\n  author\t= {Garc\\'ia-Olaya, \\'Angel and Sergio Jim\\'enez and Carlos\n\t\t  {Linares L\\'opez}},\n  title\t\t= {The 2011 International Planning Competition},\n  institution\t= {Universidad Carlos III de Madrid},\n  year\t\t= 2011,\n  address\t= {Madrid, Spain},\n  month\t\t= jul,\n  note\t\t= {http://hdl.handle.net/10016/11710}\n}\n\n

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\n \n\n \n \n \n \n \n \n Size-Independent Additive Pattern Databases for the Pancake Problem.\n \n \n \n \n\n\n \n Torralba, Á.; and Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Fourth International Symposium on Combinatorial Search, pages 164–171, Cardona (Barcelona), July 2011. \n \n\n\n\n
\n\n\n\n \n \n $\"Size-Independent$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  torralba.linares-lopez.c:size-independent,\n  author\t= {Álvaro Torralba and Carlos {Linares L\\'opez}},\n  title\t\t= {Size-Independent Additive Pattern Databases for the\n\t\t  Pancake Problem},\n  booktitle\t= {Proceedings of the Fourth International Symposium on\n\t\t  Combinatorial Search},\n  pages\t\t= {164--171},\n  year\t\t= {2011},\n  address\t= {Cardona (Barcelona)},\n  month\t\t= jul,\n  url\t\t= {http://www.aaai.org/Library/SOCS/socs11contents.php}\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Safe reinforcement learning in high-risk tasks through policy improvement.\n \n \n \n\n\n \n García Polo, F. J.; and Fernández, F.\n\n\n \n\n\n\n In IEEE SSCI 2011: Symposium Series on Computational Intelligence - ADPRL 2011: 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2011. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{GarciaPolo2011,\nabstract = {Reinforcement Learning (RL) methods are widely used for dynamic control tasks. In many cases, these are high risk tasks where the trial and error process may select actions which execution from unsafe states can be catastrophic. In addition, many of these tasks have continuous state and action spaces, making the learning problem harder and unapproachable with conventional RL algorithms. So, when the agent begins to interact with a risky and large state-action space environment, an important question arises: how can we avoid that the exploration of the state-action space causes damages in the learning (or other) systems. In this paper, we define the concept of risk and address the problem of safe exploration in the context of RL. Our notion of safety is concerned with states that can lead to damage. Moreover, we introduce an algorithm that safely improves suboptimal but robust behaviors for continuous state and action control tasks, and that learns efficiently from the experience gathered from the environment. We report experimental results using the helicopter hovering task from the RL Competition. {\\textcopyright} 2011 IEEE.},\nauthor = {{Garc{\\'{i}}a Polo}, Francisco Javier and Fern{\\'{a}}ndez, Fernando},\nbooktitle = {IEEE SSCI 2011: Symposium Series on Computational Intelligence - ADPRL 2011: 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning},\ndoi = {10.1109/ADPRL.2011.5967356},\nisbn = {9781424498888},\ntitle = {{Safe reinforcement learning in high-risk tasks through policy improvement}},\nyear = {2011}\n}\n

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\n \n\n \n \n \n \n \n \n Autonomous mobile robot control and learning with the PELEA architecture.\n \n \n \n \n\n\n \n Quintero, E.; Alcázar, V.; Borrajo, D.; Fdez-Olivares, J.; Fernández, F.; García-Olaya, Á.; Guzmán, C.; Onaindía, E.; and Prior, D.\n\n\n \n\n\n\n In Automated Action Planning for Autonomous Mobile Robots: 2011 AAAI Workshop (WS-11-09), volume WS-11-09, 2011. \n \n\n\n\n
\n\n\n\n \n \n $\"Autonomous$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Quintero2011,\nabstract = {In this paper we describe the integration of a robot control platform (Player/Stage) and a real robot (Pioneer P3DX) with PELEA (Planning, Execution and LEarning Architecture). PELEA is a general-purpose planning architecture suitable for a wide range of real world applications, from robotics to emergency management. It allows planning engineers to generate planning applications since it integrates planning, execution, replanning, monitoring and learning capabilities. We also present a relational learning approach for automatically modeling robot-action execution durations, with the purpose of improving the planning process of PELEA by refining domain definitions.},\nauthor = {Quintero, E. and Alc{\\'{a}}zar, V. and Borrajo, D. and Fdez-Olivares, J. and Fern{\\'{a}}ndez, F. and Garc{\\'{i}}a-Olaya, {\\'{A}}. and Guzm{\\'{a}}n, C. and Onaind{\\'{i}}a, E. and Prior, D.},\nbooktitle = {Automated Action Planning for Autonomous Mobile Robots: 2011 AAAI Workshop (WS-11-09)},\nfile = {:home/fernando/papers/tmp/3885-16668-1-PB.pdf:pdf},\nisbn = {9781577355250},\ntitle = {{Autonomous mobile robot control and learning with the PELEA architecture}},\nurl = {https://www.aaai.org/ocs/index.php/WS/AAAIW11/paper/view/3885},\nvolume = {WS-11-09},\nyear = {2011}\n}\n

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\n \n\n \n \n \n \n \n \n Business Simulators for Business Education and Research.\n \n \n \n \n\n\n \n Borrajo, F.; Bueno, Y.; Fernández, F.; García, J.; de Pablo, I.; Sagredo, I.; and Santos, B.\n\n\n \n\n\n\n In Computer Games as Educational and Management Tools, 14, pages 229–246. IGI Global, 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Business$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{Borrajo2011,\nabstract = {Business Simulators provide a simulated environment where different scenarios and decisions can be tested without risk. They are also used for education where they can help students to understand the main concepts and theory involved in business administration. In addition, business simulators can be used to carry out research in different scientific areas, such as psychology, financial planning, risk evaluation, or intelligent business. This paper introduces SIMBA, a new simulator for business education and research. SIMBA has two main goals. The first one is to serve as a web-based platform for business education. It permits students to connect the simulator from any point on the web, permitting both classroom education as well as distance education. SIMBA architecture permits not only the connection of human business managers, but also software agents. Thus, the second goal of SIMBA is to provide an environment in which to design and test a Multi-Agent platform for the creation, development and evaluation of Intelligent Agents that can manage companies in the same way as humans. Thus, SIMBA opens up a wide field of research between Artificial Intelligence and Business Management aimed at developing efficient intelligent agents humans can compete with. {\\textcopyright} 2011, IGI Global.},\nauthor = {Borrajo, Fernando and Bueno, Yolanda and Fern{\\'{a}}ndez, Fernando and Garc{\\'{i}}a, Javier and de Pablo, Isidro and Sagredo, Ismael and Santos, Bego{\\~{n}}a},\nbooktitle = {Computer Games as Educational and Management Tools},\nchapter = {14},\ndoi = {10.4018/978-1-60960-569-8.ch014},\nfile = {:home/fernando/papers/propios/publicados/libro/business-simulators-for-business-education-and-research.pdf:pdf},\nisbn = {9781609605698},\npages = {229--246},\npublisher = {IGI Global},\ntitle = {{Business Simulators for Business Education and Research}},\nurl = {http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-60960-569-8.ch014},\nyear = {2011}\n}\n

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\n \n\n \n \n \n \n \n \n Control of autonomous mobile robots with automated planning.\n \n \n \n \n\n\n \n Quintero Barrios, E.; García Olaya, Á.; Borrajo Millán, D.; and Fernández Rebollo, F.\n\n\n \n\n\n\n Journal of Physical Agents (JoPha), 5(1): 3–13. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Control$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{QuinteroBarrios2011,\nabstract = {In this paper we present an approach for the control of autonomous robots, based on Automated Planning (AP) techniques, where a control architecture was developed (ROPEM: RObot Plan Execution with Monitoring). The proposed architecture is composed of a set of modules that integrates deliberation with a standard planner, execution, monitoring and replanning. We avoid robotic-device and platform dependency by using a low level control layer, implemented in the Player framework, separated from the high level task execution that depends on the domain we are working on; that way we also ensure reusability of the high and low level layers. As robot task execution is non-deterministic, we can not predict the result of performing a given action and for that reason we also use a module that supervises the execution and detects when we have reached the goals or an unexpected state. Separated from the execution, we included a planning module in charge of determining the actions that will let the robot achieve its high level goals. In order to test the performance of our contribution we conducted a set of experiments on the International Planning Competition (IPC) domain Rovers, with a real robot (Pioneer P3DX). We tested the planning/replanning capabilities of the ROPEM architecture with different controlled sources of uncertainty.},\nauthor = {{Quintero Barrios}, Ezequiel and {Garc{\\'{i}}a Olaya}, {\\'{A}}ngel and {Borrajo Mill{\\'{a}}n}, Daniel and {Fern{\\'{a}}ndez Rebollo}, Fernando},\ndoi = {10.14198/JoPha.2011.5.1.02},\nfile = {:home/fernando/papers/tmp/JoPha{\\_}5{\\_}1{\\_}02.pdf:pdf},\nissn = {1888-0258},\njournal = {Journal of Physical Agents (JoPha)},\nkeywords = {Automated planning,Autonomous robots,Mobile robots,Robotic architectures},\nnumber = {1},\npages = {3--13},\ntitle = {{Control of autonomous mobile robots with automated planning}},\nurl = {http://hdl.handle.net/10045/16643},\nvolume = {5},\nyear = {2011}\n}\n

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\n \n\n \n \n \n \n \n \n Proceedings of the Fourth International Symposium on Combinatorial Search.\n \n \n \n \n\n\n \n Borrajo, D.; Likhachev, M.; and Linares-López, C.,\n editors.\n \n\n\n \n\n\n\n AAAI Press. Cardona (Spain), July 2011.\n ISBN 978-1-57735-537-3\n\n\n\n
\n\n\n\n \n \n $\"Proceedings$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@proceedings{socs11,\n\n  title = {{Proceedings of the Fourth International Symposium on Combinatorial Search}},\n\n  year = {2011},\n\n  editor = {Daniel Borrajo and Max Likhachev and Carlos Linares-López},\n\n  publisher = {AAAI Press},\n\n  address = {Cardona (Spain)},\n\n  month = {July},\n\n  cicyt = {editor},\n\n  key = {Planning-Learning},\n\n  url = {http://www.aaai.org/Library/SOCS/socs11contents.php},\n\n  note = {ISBN 978-1-57735-537-3}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using Relaxed Plan Heuristic to Select Goals in Oversubscription Planning Problems.\n \n \n \n \n\n\n \n García-Olaya, A.; de la Rosa, T.; and Borrajo, D.\n\n\n \n\n\n\n In Advances in Artificial Intelligence, volume 7023/2011, of Lecture Notes on Computer Science, pages 183–192, 2011. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ln-caepia11,\n\n  author = {Angel García-Olaya and Tomás de la Rosa and Daniel Borrajo},\n\n  booktitle = {Advances in Artificial Intelligence},\n\n  title = {Using Relaxed Plan Heuristic to Select Goals in Oversubscription Planning Problems},\n\n  year = {2011},\n\n  key = {Planning-Learning},\n\n  url = {http://hdl.handle.net/10016/12968},\n\n  volume = {7023/2011},\n\n  pages = {183--192},\n\n  optmonth = {November},\n\n  optaddress = {La Laguna (Spain)},\n\n  publisher = {Springer Verlag},\n\n  series = {Lecture Notes on Computer Science},\n\n  opteditor = {José A. Lozano and José A. Gámez and José A. Moreno},\n\n  cicyt = {lncs},\n\n  note = {},\n\n  annote = {Best paper award. http://dx.doi.org/10.1007/978-3-642-25274-7\\_19. Current Topics in Artificial Intelligence. 14th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2011.  ISBN 978-3-642-25273-0}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Adapting an RRT for Automated Planning.\n \n \n \n \n\n\n \n Alcázar, V.; Veloso, M.; and Borrajo, D.\n\n\n \n\n\n\n In Borrajo, D.; Linares-López, C.; and Likhachev, M., editor(s), Proceedings of the Fourth International Symposium on Combinatorial Search (SoCS-2011), pages 2-9, Cardona (Spain), 2011. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Adapting$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{socs11-rrt,\n\n  author = {Vidal Alcázar and Manuela Veloso and Daniel Borrajo},\n\n  booktitle = {Proceedings of the Fourth International Symposium on Combinatorial Search (SoCS-2011)},\n\n  title = {Adapting an {RRT} for Automated Planning},\n\n  publisher = {AAAI Press},\n\n  year = {2011},\n\n  key = {Planning-Learning},\n\n  url = {http://www.aaai.org/ocs/index.php/SOCS/SOCS11/paper/view/4021},\n\n  editor = {Daniel Borrajo and Carlos Linares-López and Max Likhachev},\n\n  address = {Cardona (Spain)},\n\n  pages = {2-9},\n\n  cicyt = {congresos},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Autonomous Mobile Robot Control and Learning with PELEA Architecture.\n \n \n \n \n\n\n \n Quintero, E.; Alcázar, V.; Borrajo, D.; Fdez-Olivares, J.; Fernández, F.; García-Olaya, Á.; Guzmán, C.; Onaindía, E.; and Prior, D.\n\n\n \n\n\n\n In Sariel-Talay, S.; Smith, S.; and Onder, N., editor(s), Working Notes of the AAAI'11 Workshop on Automated Action Planning for Autonomous Mobile Robots (PAMR'11), pages 51–56, San Francisco (USA), August 2011. AAAI, AAAI Press\n Technical Report WS-11-04\n\n\n\n
\n\n\n\n \n \n $\"Autonomous$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{pamr11,\n\n  author = {Ezequiel Quintero and Vidal Alcázar and Daniel Borrajo and Juan Fdez-Olivares and Fernando Fernández and Ángel García-Olaya and César Guzmán and Eva\n\n                  Onaindía and David Prior},\n\n  title = {Autonomous Mobile Robot Control and Learning with PELEA Architecture},\n\n  booktitle = {Working Notes of the AAAI'11 Workshop on Automated Action Planning for Autonomous Mobile Robots (PAMR'11)},\n\n  key = {Planning-Learning},\n\n  url = {pamr11.pdf},\n\n  editor = {Sanem Sariel-Talay and Stephen Smith and Nilufer Onder},\n\n  year = {2011},\n\n  cicyt = {workshops},\n\n  organization = {AAAI},\n\n  publisher = {AAAI Press},\n\n  address = {San Francisco (USA)},\n\n  month = {August},\n\n  pages = {51--56},\n\n  note = {Technical Report WS-11-04},\n\n  optannote = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Scaling up Heuristic Planning with Relational Decision Trees.\n \n \n \n \n\n\n \n de la Rosa, T.; Jiménez, S.; Fuentetaja, R.; and Borrajo, D.\n\n\n \n\n\n\n Journal of Artificial Intelligence Research, 40: 767–813. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Scaling$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 13 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ROLLER_JAIR2011,\n\n  author = {Tomás de la Rosa and Sergio Jiménez and Raquel Fuentetaja and Daniel Borrajo},\n\n  title = {Scaling up Heuristic Planning with Relational Decision Trees},\n\n  journal = {Journal of Artificial Intelligence Research},\n\n  year = {2011},\n\n  key = {Planning-Learning},\n\n  volume = {40},\n\n  url = {http://www.jair.org/media/3231/live-3231-5615-jair.pdf},\n\n  cicyt = {revista},\n\n  jcr = {Q3, 2011: 1.143 (59/111)},\n\n  pages = {767--813},\n\n  optannote = {http://dx.doi.org/10.1613/jair.3231}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Dynamic Sliding Window for Activity Recognition.\n \n \n \n \n\n\n \n Ortiz-Laguna, J.; García-Olaya, A.; and Borrajo, D.\n\n\n \n\n\n\n In Konstan, J.; Conejo, R.; Marzo, J. L.; and Oliver, N., editor(s), User Modeling, Adaptation and Personalization: 19th International Conference, UMAP 2011, volume LNCS 6787, of Lecture Notes on Computer Science, pages 219–230, Girona (Spain), July 2011. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{umap11,\n\n  author = {Javier Ortiz-Laguna and Angel García-Olaya and Daniel Borrajo},\n\n  title = {A Dynamic Sliding Window for Activity Recognition},\n\n  booktitle = {User Modeling, Adaptation and Personalization: 19th International Conference, UMAP 2011},\n\n  url = {umap11.pdf},\n\n  key = {Planning-Learning},\n\n  editor = {Joseph Konstan and Ricardo Conejo and José L. Marzo and Nuria Oliver},\n\n  year = {2011},\n\n  publisher = {Springer Verlag},\n\n  series = {Lecture Notes on Computer Science},\n\n  address = {Girona (Spain)},\n\n  month = {July},\n\n  volume = {LNCS 6787},\n\n  pages = {219--230},\n\n  note = {},\n\n  cicyt = {lncs},\n\n  jcr = {B},\n\n  optannote = {was A in 2010}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Planning Multi-modal Transportation Problems.\n \n \n \n \n\n\n \n Flórez, J. E.; Torralba, Á.; García, J.; Linares-López, C.; García-Olaya, Á.; and Borrajo, D.\n\n\n \n\n\n\n In , editor(s), Proceedings of ICAPS'11, Freiburg (Germany), June 2011. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Planning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icaps11,\n\n  author = {José E. Flórez and Álvaro Torralba and Javier García and Carlos Linares-López and Ángel García-Olaya and Daniel Borrajo},\n\n  booktitle = {Proceedings of ICAPS'11},\n\n  title = {Planning Multi-modal Transportation Problems},\n\n  publisher = {AAAI Press},\n\n  year = {2011},\n\n  key = {Planning-Learning},\n\n  url = {http://aaai.org/ocs/index.php/ICAPS/ICAPS11/paper/view/2701},\n\n  editor = {},\n\n  volume = {},\n\n  series = {},\n\n  address = {Freiburg (Germany)},\n\n  month = {June},\n\n  pages = {},\n\n  cicyt = {congresos-buenos},\n\n  note = {},\n\n  jcr = {A*}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Control of Autonomous Mobile Robots with Automated Planning.\n \n \n \n \n\n\n \n Quintero, E.; García-Olaya, Á.; Borrajo, D.; and Fernández, F.\n\n\n \n\n\n\n Journal of Physical Agents, 5(1): 3-13. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Control$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jopha11,\n\n  author = {Ezequiel Quintero and Ángel García-Olaya and Daniel Borrajo and Fernando Fernández},\n\n  title = {Control of Autonomous Mobile Robots with Automated Planning},\n\n  journal = {Journal of Physical Agents},\n\n  optcrossref = {},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista-noJCR},\n\n  url = {http://www.jopha.net/index.php/jopha/article/view/81},\n\n  opteditor = {},\n\n  volume = {5},\n\n  number = {1},\n\n  optseries = {},\n\n  year = {2011},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {},\n\n  month = {},\n\n  pages = {3-13},\n\n  note = {},\n\n  optannote = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n A SAT Compilation of the Landmark Graph .\n \n \n \n\n\n \n Alcázar, V.; and Veloso, M.\n\n\n \n\n\n\n In Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS), pages 47-54, 2011. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{alcazar2011,\n\n  author = {Vidal Alc\\'azar and Manuela Veloso},\n\n  title = {A {SAT} Compilation of the Landmark Graph },\n\n  booktitle = {Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS)},\n\n  key = {Planning-Learning},\n\n  year = {2011},\n\n  pages = {47-54}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Size-Independent Additive Pattern Databases for the Pancake Problem.\n \n \n \n\n\n \n Torralba Arias de Reyna, Á.; and Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Fourth International Symposium on Combinatorial Search, pages 164–171, Cardona (Barcelona), July 2011. \n \n\n\n\n
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@inproceedings{alvaro-torralba-arias-de-reyna.cll:size-independent,\n\n  author = {\\'Alvaro {Torralba Arias de Reyna} and Carlos {Linares L\\'opez}},\n\n  title = {Size-Independent Additive Pattern Databases for the Pancake Problem},\n\n  key = {Search},\n\n  booktitle = {Proceedings of the Fourth International Symposium on Combinatorial Search},\n\n  pages = {164--171},\n\n  year = {2011},\n\n  address = {Cardona (Barcelona)},\n\n  month = jul\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n A Similarity Function with Local Feature Weighting for Structured Data.\n \n \n \n\n\n \n Suárez, R.; García-Durán, R.; and Fernández, F.\n\n\n \n\n\n\n In Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'01), 2011. \n \n\n\n\n
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@inproceedings{suarez11,\n\n  author = {Rub\\'en Su\\'arez and Roc\\'io Garc\\'ia-Dur\\'an and Fernando Fern\\'andez},\n\n  title = {A Similarity Function with Local Feature Weighting for Structured Data},\n\n  booktitle = {Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'01)},\n\n  key = {Learning-Information Retrieval},\n\n  year = {2011},\n\n  optpages = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Computer Games as Educational and Management Tools: Uses and Approaches.\n \n \n \n\n\n \n Borrajo, F.; Bueno, Y.; Fernández, F.; de Pablo, I.; García, J.; Sagredo, I.; and Santos, B.\n\n\n \n\n\n\n Business, Technological and Social Dimensions of Computer Games: Multidisciplinary Developments. IGI Global, 2011.\n \n\n\n\n
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@inbook{simba-igi,\n\n  author = {Fernando Borrajo and Yolanda Bueno and Fernando Fern\\'andez and Isidro de Pablo and Javier Garc\\'ia and Ismael Sagredo and Begoña Santos},\n\n  title = {Business, Technological and Social Dimensions of Computer Games: Multidisciplinary Developments},\n\n  chapter = {Computer Games as Educational and Management Tools: Uses and Approaches},\n\n  key = {Other},\n\n  publisher = {IGI Global},\n\n  year = {2011}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Safe Reinforcement Learning in High-Risk Tasks through Policy Improvement.\n \n \n \n\n\n \n García, J.; and Fernández, F.\n\n\n \n\n\n\n In Proceedings of the 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2011. \n \n\n\n\n
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@inproceedings{garcia11,\n\n  author = {Javier Garc\\'ia and Fernando Fern\\'andez},\n\n  title = {Safe Reinforcement Learning in High-Risk Tasks through Policy Improvement},\n\n  booktitle = {Proceedings of the 2011 IEEE Symposium  on Adaptive Dynamic Programming and Reinforcement Learning},\n\n  key = {Reactive},\n\n  optpages = {},\n\n  year = {2011}\n\n}\n\n\n\n

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\n \n 2010\n \n \n (25)\n \n \n

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\n \n\n \n \n \n \n \n \n TIMIPLAN: An Application to Solve Multimodal Transportation Problems.\n \n \n \n \n\n\n \n Flórez, J. E.; Torralba, Á.; García, J.; Linares López, C.; García-Olaya, Á.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of \"Scheduling and Planning Applications woRKshop\" (SPARK). Workshop of the Twentieth International Conference on Automated Planning and Scheduling (ICAPS'10), Toronto, Ontario (Canada), May 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"TIMIPLAN:$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  florez.je.torralba.ea:timiplan-,\n  author\t= {Jos\\'e E. Fl\\'orez and Álvaro Torralba and Javier García\n\t\t  and Carlos {Linares L\\'opez} and Ángel García-Olaya and\n\t\t  Daniel Borrajo},\n  title\t\t= {{TIMIPLAN:} An Application to Solve Multimodal\n\t\t  Transportation Problems},\n  booktitle\t= {Proceedings of "Scheduling and Planning Applications\n\t\t  woRKshop" (SPARK). Workshop of the Twentieth International\n\t\t  Conference on Automated Planning and Scheduling\n\t\t  (ICAPS'10)},\n  year\t\t= 2010,\n  address\t= {Toronto, Ontario (Canada)},\n  month\t\t= may,\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/spark2010-workshop.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Adding Diversity to Classical Heuristic Planning.\n \n \n \n \n\n\n \n Linares López, C.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the Third Annual Symposium on Combinatorial Search (SOCS'10), pages 73–80, Atlanta, USA, July 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"Adding$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c.borrajo.d:adding,\n  author\t= {Carlos {Linares L\\'opez} and Daniel Borrajo},\n  title\t\t= {Adding Diversity to Classical Heuristic Planning},\n  booktitle\t= {Proceedings of the Third Annual Symposium on Combinatorial\n\t\t  Search (SOCS'10)},\n  pages\t\t= {73--80},\n  year\t\t= {2010},\n  address\t= {Atlanta, USA},\n  month\t\t= jul,\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/socs2010.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Vectorial Pattern Databases.\n \n \n \n \n\n\n \n Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Nineteenth European Conference on Artificial Intelligence (ECAI'10), pages 1059–1060, Lisbon, Portugal, August 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"Vectorial$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c:vectorial,\n  author\t= {Carlos {Linares L\\'opez}},\n  title\t\t= {Vectorial Pattern Databases},\n  booktitle\t= {Proceedings of the Nineteenth European Conference on\n\t\t  Artificial Intelligence (ECAI'10)},\n  pages\t\t= {1059--1060},\n  year\t\t= 2010,\n  address\t= {Lisbon, Portugal},\n  month\t\t= aug,\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/ecai2010.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n SIMBA: A simulator for business education and research.\n \n \n \n\n\n \n Borrajo, F.; Bueno, Y.; de Pablo, I.; Santos, B.; Fernández, F.; García, J.; and Sagredo, I.\n\n\n \n\n\n\n Decision Support Systems, 48(3). 2010.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Borrajo2010,\nabstract = {Business simulators are used for decision-making since different scenarios can be evaluated without risk. They are also used in business management education. The main goal of this paper is to introduce SIMBA (SIMulator for Business Administration), a new simulator that serves as a web-based platform for business education, permitting both classroom and distance education. This paper also adds a research aspect in business intelligence because SIMBA can be used as a fieldwork tool for the development and evaluation of intelligent agents. The simulator creates a more complex competitive environment in which intelligent agents play the role of business decision makers. {\\textcopyright} 2009 Elsevier B.V. All rights reserved.},\nauthor = {Borrajo, F. and Bueno, Y. and de Pablo, I. and Santos, B. and Fern{\\'{a}}ndez, F. and Garc{\\'{i}}a, J. and Sagredo, I.},\ndoi = {10.1016/j.dss.2009.06.009},\nissn = {01679236},\njournal = {Decision Support Systems},\nkeywords = {Business education,Business intelligence,Business simulator,Multi-agent systems},\nnumber = {3},\ntitle = {{SIMBA: A simulator for business education and research}},\nvolume = {48},\nyear = {2010}\n}\n

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\n \n\n \n \n \n \n \n Business simulation in business education.\n \n \n \n\n\n \n Borrajo, F.; Bueno, Y.; Fernández, F.; García, J.; de Pablo, I.; Sagredo, I.; and Santos, B.\n\n\n \n\n\n\n 2010.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@book{Borrajo2010a,\nabstract = {This paper introduces SIMBA, a new simulator for business education and research. SIMBA has two main goals. The first one is to serve as a web-based platform for business education. It allows students to connect the simulator from any point on the Web, permitting both classroom education as well as distance education. This circumstance, per se, provides an interesting research field in distance education. Furthermore, SIMBA architecture permits not only the connection of human business managers, but also software agents. So, the second goal of SIMBA is to serve as a Multi- Agent platform for the creation, development and evaluation of Intelligent Agents, which can manage companies in the same way as humans, thus creating a challenging competition environment both for students and for researchers in business modeling and Artificial Intelligence. Decision-making in SIMBA is a challenge, since it requires handling large and continuous state and action spaces. In this chapter, we propose to tackle this problem using Reinforcement Learning (RL) and K-Nearest Neighbors (KNN) approaches. We demonstrate that learning agents are very competitive, and they can outperform human expert decision strategies from business literature. {\\textcopyright} 2011 Nova Science Publishers, Inc. All rights reserved.},\nauthor = {Borrajo, F. and Bueno, Y. and Fern{\\'{a}}ndez, F. and Garc{\\'{i}}a, J. and de Pablo, I. and Sagredo, I. and Santos, B.},\nbooktitle = {Distance Education},\nisbn = {9781617610431},\nkeywords = {Business education,Business games,Business intelligence,Business simulator,Data-mining,KNN,Learning agents,Multi agent systems,Reinforcement learning},\ntitle = {{Business simulation in business education}},\nyear = {2010}\n}\n

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\n \n\n \n \n \n \n \n A reinforcement learning approach for multiagent navigation.\n \n \n \n\n\n \n Martinez-Gil, F.; Barber, F.; Lozano, M.; Grimaldo, F.; and Fernández, F.\n\n\n \n\n\n\n In ICAART 2010 - 2nd International Conference on Agents and Artificial Intelligence, Proceedings, volume 1, 2010. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@inproceedings{Martinez-Gil2010,\nabstract = {This paper presents a Q-Learning-based multiagent system oriented to provide navigation skills to simulation agents in virtual environments. We focus on learning local navigation behaviours from the interactions with other agents and the environment. We adopt an environment-independent state space representation to provide the required scalability of such kind of systems. In this way, we evaluate whether the learned action-value functions can be transferred to other agents to increase the size of the group without loosing behavioural quality. We explain the learning process defined and the the results of the collective behaviours obtained in a well-known experiment in multiagent navigation: the exit of a place through a door.},\nauthor = {Martinez-Gil, F. and Barber, F. and Lozano, M. and Grimaldo, F. and Fern{\\'{a}}ndez, Fernando},\nbooktitle = {ICAART 2010 - 2nd International Conference on Agents and Artificial Intelligence, Proceedings},\nfile = {:home/fernando/papers/tmp/567c84d2d748104a5cfaec7e08062f1a9914.pdf:pdf},\nisbn = {9789896740221},\nkeywords = {Local navigation,Multiagent systems,Reinforcement learning},\ntitle = {{A reinforcement learning approach for multiagent navigation}},\nvolume = {1},\nyear = {2010}\n}\n

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\n \n\n \n \n \n \n \n \n Learning virtual agents for decision-making in business simulators.\n \n \n \n \n\n\n \n García, J.; Fernández, F.; and Borrajo, F.\n\n\n \n\n\n\n In Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010), volume 627, 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Garcia2010,\nabstract = {In this paper we describe SIMBA, a simulator for business administration, as a Multi-Agent platform for the design, implementation and evaluation of virtual agents. SIMBA creates a complex competitive environment in which intelligent agents play the role of business decision makers. An important issue of SIMBA architecture is that humans can interact with virtual agents. Decision making in SIMBA is a challenge, since it requires handling large and continuous state and action spaces. In this paper, we propose to tackle this problem using Reinforcement Learning (RL) and K-Nearest Neighbors (KNN) approaches. RL requires the use of generalization techniques to be applied in large state and action spaces. We present different combinations in the choice of the generalization method based on Vector Quantization (VQ) and CMAC. We demonstrate that learning agents are very competitive, and they can outperform human expert decision strategies from business literature.},\nauthor = {Garc{\\'{i}}a, J. and Fern{\\'{a}}ndez, F. and Borrajo, F.},\nbooktitle = {Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)},\nfile = {:home/fernando/papers/tmp/mass{\\_}2.pdf:pdf},\nissn = {16130073},\ntitle = {{Learning virtual agents for decision-making in business simulators}},\nurl = {http://ceur-ws.org/Vol-627/},\nvolume = {627},\nyear = {2010}\n}\n

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\n \n\n \n \n \n \n \n A similarity function with local feature weighting for structured data.\n \n \n \n\n\n \n Suárez, R.; García-Durán, R.; and Fernández, F.\n\n\n \n\n\n\n In ESANN 2011 proceedings, 19th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 2010. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Suarez2010,\nabstract = {The application of learning approaches as Kernel or Instance Based methods to tree structured data requires the definition of similarity functions able to deal with such data. A new similarity function for nearest prototype classification in relational data that follows a tree structure is defined in this paper. Its main characteristic is its capability to weight the importance of the different data features in different areas of the feature space. This work is built over two previous ideas: a similarity function for Local Feature Weighting (LFW), and a Relational Nearest Prototype Classification algorithm (RNPC).},\nauthor = {Su{\\'{a}}rez, R. and Garc{\\'{i}}a-Dur{\\'{a}}n, R. and Fern{\\'{a}}ndez, F.},\nbooktitle = {ESANN 2011 proceedings, 19th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning},\nfile = {:home/fernando/papers/tmp/es2011-61.pdf:pdf},\nisbn = {9782874190445},\ntitle = {{A similarity function with local feature weighting for structured data}},\nyear = {2010}\n}\n

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\n \n\n \n \n \n \n \n \n Probabilistic Policy Reuse for inter-task transfer learning.\n \n \n \n \n\n\n \n Fernández, F.; García, J.; and Veloso, M.\n\n\n \n\n\n\n Robotics and Autonomous Systems, 58(7): 866–871. jul 2010.\n \n\n\n\n
\n\n\n\n \n \n $\"Probabilistic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Fernandez2010,\nabstract = {Policy Reuse is a reinforcement learning technique that efficiently learns a new policy by using past similar learned policies. The Policy Reuse learner improves its exploration by probabilistically including the exploitation of those past policies. Policy Reuse was introduced, and its effectiveness was previously demonstrated, in problems with different reward functions in the same state and action spaces. In this article, we contribute Policy Reuse as transfer learning among different domains. We introduce extended Markov Decision Processes (MDPs) to include domains and tasks, where domains have different state and action spaces, and tasks are problems with different rewards within a domain. We show how Policy Reuse can be applied among domains by defining and using a mapping between their state and action spaces. We use several domains, as versions of a simulated RoboCup Keepaway problem, where we show that Policy Reuse can be used as a mechanism of transfer learning significantly outperforming a basic policy learner. {\\textcopyright} 2010 Elsevier B.V. All rights reserved.},\nauthor = {Fern{\\'{a}}ndez, Fernando and Garc{\\'{i}}a, Javier and Veloso, Manuela},\ndoi = {10.1016/j.robot.2010.03.007},\nfile = {:home/fernando/papers/tmp/1-s2.0-S0921889010000655-main.pdf:pdf},\nissn = {09218890},\njournal = {Robotics and Autonomous Systems},\nkeywords = {Policy Reuse,Reinforcement learning,Transfer learning},\nmonth = {jul},\nnumber = {7},\npages = {866--871},\ntitle = {{Probabilistic Policy Reuse for inter-task transfer learning}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S0921889010000655},\nvolume = {58},\nyear = {2010}\n}\n

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\n \n\n \n \n \n \n \n \n \\sc pelea: Planning, Learning and Execution Architecture.\n \n \n \n \n\n\n \n Alcázar, V.; Guzmán, C.; Prior, D.; Borrajo, D.; Castillo, L.; and Onaindia, E.\n\n\n \n\n\n\n In , editor(s), Proceedings of the 28th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG'10), pages 17-24, Brescia (Italia), December 2010. \n \n\n\n\n
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@inproceedings{plansig10,\n\n  author = {Vidal Alcázar and César Guzmán and David Prior and Daniel Borrajo and Luis Castillo and Eva Onaindia},\n\n  title = {{\\sc pelea}: Planning, Learning and Execution Architecture},\n\n  booktitle = {Proceedings of the 28th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG'10)},\n\n  url = {plansig10.pdf},\n\n  key = {Planning-Learning},\n\n  cicyt = {workshops},\n\n  editor = {},\n\n  year = {2010},\n\n  address = {Brescia (Italia)},\n\n  month = {December},\n\n  pages = {17-24},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Improving the Execution of KDD Workflows Generated by AI Planners.\n \n \n \n \n\n\n \n Fernández, S.; Suárez, R.; de la Rosa, T.; Ortiz, J.; Fernández, F.; Borrajo, D.; and Manzano, D.\n\n\n \n\n\n\n In , editor(s), Proceedings of the ECAI'10 3rd Planning to Learn Workshop (PlanLearn), Lisboa (Portugal), August 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"Improving$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{planlearn10,\n\n  author = {Susana Fernández and Ruben Suárez and Tomás de la Rosa and Javier Ortiz and Fernando Fernández and Daniel Borrajo and David Manzano},\n\n  booktitle = {Proceedings of the ECAI'10 3rd Planning to Learn Workshop (PlanLearn)},\n\n  title = {Improving the Execution of {KDD} Workflows Generated by {AI} Planners},\n\n  publisher = {},\n\n  year = {2010},\n\n  key = {Planning-Learning},\n\n  url = {planlearn10.pdf},\n\n  editor = {},\n\n  volume = {},\n\n  series = {},\n\n  address = {Lisboa (Portugal)},\n\n  month = {August},\n\n  pages = {},\n\n  cicyt = {workshops},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Map-Merging-Free Connectivity Positioning for Distributed Robot Teams.\n \n \n \n \n\n\n \n Liemhetcharat, S.; Veloso, M.; Melo, F.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the 11th International Conference on Intelligent Autonomous Systems, Ottawa (Canada), 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"Map-Merging-Free$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ias10-robots,\n\n  author = {Somchaya Liemhetcharat and Manuela Veloso and Francisco Melo and Daniel Borrajo},\n\n  title = {Map-Merging-Free Connectivity Positioning for Distributed Robot Teams},\n\n  booktitle = {Proceedings of the 11th International Conference on Intelligent Autonomous Systems},\n\n  optcrossref = {},\n\n  key = {Planning-Learning},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  url = {ias10-robots.pdf},\n\n  year = {2010},\n\n  cicyt = {congresos},\n\n  organization = {},\n\n  publisher = {},\n\n  address = {Ottawa (Canada)},\n\n  month = {},\n\n  optpages = {},\n\n  note = {},\n\n  optannote = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Adding Diversity to Classical Heuristic Planning.\n \n \n \n \n\n\n \n Linares-López, C.; and Borrajo, D.\n\n\n \n\n\n\n In Sturtevant, N.; and Felner, A., editor(s), Proceedings of Third International Symposium on Combinatorial Search (SoCS-2010), Atlanta (USA), 2010. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Adding$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{socs10,\n\n  author = {Carlos Linares-López and Daniel Borrajo},\n\n  booktitle = {Proceedings of Third International Symposium on Combinatorial Search (SoCS-2010)},\n\n  title = {Adding Diversity to Classical Heuristic Planning},\n\n  publisher = {AAAI Press},\n\n  year = {2010},\n\n  key = {Planning-Learning},\n\n  url = {socs10.pdf},\n\n  editor = {Nathan Sturtevant and Ariel Felner},\n\n  volume = {},\n\n  series = {},\n\n  address = {Atlanta (USA)},\n\n  pages = {},\n\n  cicyt = {congresos},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n From Unstructured Web Knowledge to Plan Descriptions.\n \n \n \n \n\n\n \n Addis, A.; and Borrajo, D.\n\n\n \n\n\n\n of Studies in Computational Intelligence. Information Retrieval and Mining in Distributed Environments, pages 41–59. Soro, A.; Vargiu, E.; Armano, G.; and Paddeu, G., editor(s). Springer Verlag, 2010.\n \n\n\n\n
\n\n\n\n \n \n $\"Information$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inbook{dart2010,\n\n  author = {Andrea Addis and Daniel Borrajo},\n\n  title = {Information Retrieval and Mining in Distributed Environments},\n\n  chapter = {From Unstructured Web Knowledge to Plan Descriptions},\n\n  url = {dart2010.pdf},\n\n  key = {Planning-Web},\n\n  cicyt = {capitulos},\n\n  publisher = {Springer Verlag},\n\n  series = {Studies in Computational Intelligence},\n\n  year = {2010},\n\n  editor = {Alessandro Soro and Eloisa Vargiu and Giuliano Armano and Gavino Paddeu},\n\n  pages = {41--59},\n\n  note = {},\n\n  annote = {ISSN: 1860-949X}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Comparative Study of Discretization Approaches for State Space Generalization in the Keepaway Soccer Task.\n \n \n \n \n\n\n \n García, J.; López-Bueno, I.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n Reinforcement Learning: Algorithms, Implementations and Applications. Nova Publishers, 2010.\n \n\n\n\n
\n\n\n\n \n \n $\"Reinforcement$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inbook{keepaway,\n\n  author = {Javier García and Iván López-Bueno and Fernando Fernández and Daniel Borrajo},\n\n  chapter = {A Comparative Study of Discretization Approaches for State Space Generalization in the Keepaway Soccer Task},\n\n  title = {Reinforcement Learning: Algorithms, Implementations and Applications},\n\n  year = {2010},\n\n  publisher = {Nova Publishers},\n\n  series = {},\n\n  url = {keepaway.pdf},\n\n  key = {Reactive},\n\n  cicyt = {capitulos},\n\n  jcr = {},\n\n  volume = {},\n\n  number = {},\n\n  month = {},\n\n  pages = {},\n\n  note = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using Backwards Generated Goals for heuristic planning.\n \n \n \n \n\n\n \n Alcázar, V.; Borrajo, D.; and Linares-López, C.\n\n\n \n\n\n\n In , editor(s), Proceedings of ICAPS'10, pages 2–9, Toronto (Canada), May 2010. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icaps10-bidir,\n\n  author = {Vidal Alcázar and Daniel Borrajo and Carlos Linares-López},\n\n  booktitle = {Proceedings of ICAPS'10},\n\n  title = {Using Backwards Generated Goals for heuristic planning},\n\n  publisher = {AAAI Press},\n\n  year = {2010},\n\n  key = {Planning-Learning},\n\n  url = {http://www.aaai.org/ocs/index.php/ICAPS/ICAPS10/paper/view/1428},\n\n  editor = {},\n\n  volume = {},\n\n  series = {},\n\n  address = {Toronto (Canada)},\n\n  month = {May},\n\n  pages = {2--9},\n\n  cicyt = {congresos-buenos},\n\n  note = {},\n\n  jcr = {A*}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n GA-Stacking: Evolutionary Stacked Generalization.\n \n \n \n \n\n\n \n Ledezma, A.; Aler, R.; Sanchis, A.; and Borrajo, D.\n\n\n \n\n\n\n Intelligent Data Analysis, 14(1): 89-119. 2010.\n http://dx.doi.org/10.3233/IDA-2010-0410\n\n\n\n
\n\n\n\n \n \n $\"GA-Stacking:$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ida10,\n\n  author = {Agapito Ledezma and Ricardo Aler and Araceli Sanchis and Daniel Borrajo},\n\n  title = {GA-Stacking: Evolutionary Stacked Generalization},\n\n  journal = {Intelligent Data Analysis},\n\n  year = {2010},\n\n  publisher = {IOS Press},\n\n  key = {Multi-Agent Learning},\n\n  url = {http://hdl.handle.net/10016/6758},\n\n  volume = {14},\n\n  number = {1},\n\n  optmonth = {},\n\n  pages = {89-119},\n\n  cicyt = {revista},\n\n  jcr = {Q4, 2010: 0.412 (98/108)},\n\n  optjcr = {2007: 0.446 (76/93)},\n\n  note = {http://dx.doi.org/10.3233/IDA-2010-0410},\n\n  optannote = {DOI 10.3233/IDA-2009-0410}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Automatic generation of temporal planning domains for e-learning problems.\n \n \n \n \n\n\n \n Castillo, L.; Morales, L.; González-Ferrer, A.; Fdez-Olivares, J.; Borrajo, D.; and Onaindía, E.\n\n\n \n\n\n\n Journal of Scheduling, 13(4): 347-362. 2010.\n ISSN: 1094-6136 (print version), ISSN: 1099-1425 (electronic version), DOI: 10.1007/s10951-009-0140-x\n\n\n\n
\n\n\n\n \n \n $\"Automatic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{adaptaplan-jos10,\n\n  author = {Luis Castillo and Lluvia Morales and Arturo González-Ferrer and Juan Fdez-Olivares and Daniel Borrajo and Eva Onaindía},\n\n  title = {Automatic generation of temporal planning domains for e-learning problems},\n\n  journal = {Journal of Scheduling},\n\n  year = {2010},\n\n  publisher = {Springer Verlag},\n\n  key = {Planning-Learning},\n\n  url = {http://dx.doi.org/10.1007/s10951-009-0140-x},\n\n  volume = {13},\n\n  number = {4},\n\n  month = {},\n\n  pages = {347-362},\n\n  cicyt = {revista},\n\n  jcr = {Q2, Categoría: Engineering, Manufacturing. 2010: 1.297 (12/38), En Categoría Operations Research \\& Management Science: 2010 (24/75)},\n\n  optjcr = {Categoría: Engineering, Manufacturing. 2007: 1.0 (6/38), 2008: 1.050 (13/38).\\\\ En Categoría Operations Research \\& Management Science: 2007 (31/60), 2008 (24/64)},\n\n  note = {ISSN: 1094-6136 (print version), ISSN: 1099-1425 (electronic version), DOI: 10.1007/s10951-009-0140-x}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Look-ahead B&B Search for Cost-Based Planning.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; and Linares-López, C.\n\n\n \n\n\n\n In Meseguer, P.; Mandow, L.; and Martínez-Gasca, R., editor(s), Current Topics in Artficial Intelligence, CAEPIA 2009 Selected Papers, volume LNAI 5988, of Lecture Notes on Artificial Intelligence, pages 201-211, Sevilla (Spain), 2010. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ln-caepia10,\n\n  author = {Raquel Fuentetaja and Daniel Borrajo and Carlos Linares-López},\n\n  booktitle = {Current Topics in Artficial Intelligence, CAEPIA 2009 Selected Papers},\n\n  title = {A Look-ahead {B\\&B} Search for Cost-Based Planning},\n\n  publisher = {Springer Verlag},\n\n  series = {Lecture Notes on Artificial Intelligence},\n\n  year = {2010},\n\n  key = {Planning-Learning},\n\n  url = {caepia09.pdf},\n\n  editor = {Pedro Meseguer and Lawrence Mandow and Rafael Martínez-Gasca},\n\n  volume = {LNAI 5988},\n\n  address = {Sevilla (Spain)},\n\n  month = {},\n\n  pages = {201-211},\n\n  cicyt = {lncs},\n\n  note = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Learning Virtual Agents for Decision-Making in Business Simulators.\n \n \n \n\n\n \n García, J.; Borrajo, F.; and Fernández, F.\n\n\n \n\n\n\n In MALLOW (Multi-Agent Logics, Languages, and Organisations Federated Workshops) 2010 Workshop on Multi-Agent Systems and Simulation (MAS&S), 2010. \n \n\n\n\n
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@inproceedings{mallow10,\n\n  author = {Javier Garc\\'ia and Fernando Borrajo and Fernando Fern\\'andez},\n\n  title = {Learning Virtual Agents for Decision-Making in Business Simulators},\n\n  key = {Reactive},\n\n  booktitle = {MALLOW (Multi-Agent Logics, Languages, and Organisations Federated Workshops) 2010 Workshop on Multi-Agent Systems and Simulation (MAS\\&S)},\n\n  optpages = {},\n\n  year = {2010},\n\n  cicyt = {workshops}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n On the Inference of Intermediate Goals in Automated Planning.\n \n \n \n \n\n\n \n Alcázar, V.\n\n\n \n\n\n\n In Doctoral Consortium, International Conference on Automated Planning and Scheduling, 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"On$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{DBLP:conf/aips/AlcazarBL10,\n\n  author = {Vidal Alcázar},\n\n  title = {On the Inference of Intermediate Goals in Automated Planning},\n\n  booktitle = {Doctoral Consortium, International Conference on Automated Planning and Scheduling},\n\n  year = {2010},\n\n  key = {Planning-Learning},\n\n  url = {http://users.cecs.anu.edu.au/~ssanner/ICAPS_2010_DC/Abstracts/alcazar-saiz.pdf},\n\n  cicyt = {workshops}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Vectorial Pattern Databases.\n \n \n \n \n\n\n \n Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Nineteenth European Conference on Artificial Intelligence (ECAI'10), pages 1059–1060, Lisbon, Portugal, August 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"Vectorial$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{linares-lopez.c:vectorial,\n\n  author = {Carlos {Linares López}},\n\n  title = {Vectorial Pattern Databases},\n\n  booktitle = {Proceedings of the Nineteenth European Conference on\n\n          Artificial Intelligence (ECAI'10)},\n\n  pages = {1059--1060},\n\n  year = 2010,\n\n  key = {Search},\n\n  address = {Lisbon, Portugal},\n\n  month = aug,\n\n  url = {http://www.plg.inf.uc3m.es/~clinares/download/papers/ecai2010.pdf.gz},\n\n  cicyt = {congresos-buenos}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n SIMBA: A Simulator for Business Education and Research.\n \n \n \n\n\n \n Borrajo, F.; Bueno, Y.; de Pablo, I.; Santos, B.; Fernández, F.; García, J.; and Sagredo, I.\n\n\n \n\n\n\n Decision Support Systems, 48(3): 498-506. 2010.\n \n\n\n\n
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@article{dss10,\n\n  author = {Fernando Borrajo and Yolanda Bueno and Isidro de Pablo and Begoña Santos and Fernando Fernández and Javier García and Ismael Sagredo},\n\n  title = {SIMBA: A Simulator for Business Education and Research},\n\n  journal = {Decision Support Systems},\n\n  year = {2010},\n\n  volume = {48},\n\n  number = {3},\n\n  key = {Organisations modelling},\n\n  pages = {498-506},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Probabilistic Policy Reuse for Inter-Task Transfer Learning.\n \n \n \n\n\n \n Fernández, F.; García, J.; and Veloso, M.\n\n\n \n\n\n\n Robotics and Autonomous Systems, 58(7): 866-871. 2010.\n \n\n\n\n
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@article{ras10,\n\n  author = {Fernando Fern\\'andez and Javier Garc\\'ia and Manuela Veloso},\n\n  title = {Probabilistic Policy Reuse for Inter-Task Transfer Learning},\n\n  journal = {Robotics and Autonomous Systems},\n\n  year = {2010},\n\n  key = {Reactive},\n\n  pages = {866-871},\n\n  volume = {58(7)},\n\n  doi = {10.1016/j.robot.2010.03.007}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n A Reinforcement Learning approach for Multiagent Navigation.\n \n \n \n\n\n \n Martínez-Gil, F.; Barber, F.; Lozano, M.; Grimaldo, F.; and Fernández, F.\n\n\n \n\n\n\n In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART 2010), 2010. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icaart10,\n\n  author = {Francisco Martínez-Gil and Fernando Barber and Miguel Lozano and Francisco Grimaldo and Fernando Fernández},\n\n  title = {A Reinforcement Learning approach for Multiagent Navigation},\n\n  booktitle = {Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART 2010)},\n\n  key = {Reactive},\n\n  optpages = {},\n\n  year = {2010},\n\n  cicyt = {congresos}\n\n}\n\n\n\n

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\n \n 2009\n \n \n (14)\n \n \n

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\n \n\n \n \n \n \n \n \n A Look-ahead B&B Search for Cost-Based Planning.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; and Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Thirteenth Conference of the Spanish Association for Artificial Intelligence (CAEPIA'09), pages 105–114, Sevilla, Spain, November 2009. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  fuentetaja.r.borrajo.d.ea:look-ahead,\n  author\t= {Raquel Fuentetaja and Daniel Borrajo and Carlos {Linares\n\t\t  L\\'opez}},\n  title\t\t= {A Look-ahead {B}\\&{B} Search for Cost-Based Planning},\n  booktitle\t= {Proceedings of the Thirteenth Conference of the Spanish\n\t\t  Association for Artificial Intelligence (CAEPIA'09)},\n  pages\t\t= {105--114},\n  year\t\t= {2009},\n  month\t\t= nov,\n  address\t= {Sevilla, Spain},\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/caepia09.pdf.gz}\n\t\t  \n}\n\n\n

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\n \n\n \n \n \n \n \n \n A Unified View of Cost-Based Heuristics.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; and Linares López, C.\n\n\n \n\n\n\n In Proceedings of the \"2nd Workshop on Heuristics for Domain-independent Planning\". Workshop of the Nineteenth International Conference on Automated Planning and Scheduling (ICAPS'09), Thessaloniki, Greece, September 2009. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  fuentetaja.r.borrajo.d.ea:unified,\n  author\t= {Raquel Fuentetaja and Daniel Borrajo and Carlos {Linares\n\t\t  L\\'opez}},\n  title\t\t= {A Unified View of Cost-Based Heuristics},\n  booktitle\t= {Proceedings of the "2nd Workshop on Heuristics for\n\t\t  Domain-independent Planning". Workshop of the Nineteenth\n\t\t  International Conference on Automated Planning and\n\t\t  Scheduling (ICAPS'09)},\n  pages\t\t= {},\n  month\t\t= sep,\n  year\t\t= {2009},\n  address\t= {Thessaloniki, Greece},\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/icaps09-workshop.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Assisting Data Mining through Automated Planning.\n \n \n \n \n\n\n \n Fernández, F.; Borrajo, D.; Fernández, S.; and Manzano, D.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 5632 LNAI, pages 760–774. 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Assisting$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{Fernandez2009,\nabstract = {The induction of knowledge from a data set relies in the execution of multiple data mining actions: to apply filters to clean and select the data, to train different algorithms (clustering, classification, regression, association), to evaluate the results using different approaches (cross validation, statistical analysis), to visualize the results, etc. In a real data mining process, previous actions are executed several times, sometimes in a loop, until an accurate result is obtained. However, performing previous tasks requires a data mining engineer or expert which supervises the design and evaluate the whole process. The goal of this paper is to describe MOLE, an architecture to automatize the data mining process. The architecture assumes that the data mining process can be seen from a classical planning perspective, and hence, that classical planning tools can be used to design the process. MOLE is built and instantiated on the basis of i) standard languages to describe the data set and the data mining process; ii) available tools to design, execute and evaluate the data mining processes. {\\textcopyright} 2009 Springer Berlin Heidelberg.},\nauthor = {Fern{\\'{a}}ndez, Fernando and Borrajo, Daniel and Fern{\\'{a}}ndez, Susana and Manzano, David},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\ndoi = {10.1007/978-3-642-03070-3_57},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F978-3-642-03070-3{\\_}57.pdf:pdf},\nisbn = {3642030696},\nissn = {03029743},\npages = {760--774},\ntitle = {{Assisting Data Mining through Automated Planning}},\nurl = {http://link.springer.com/10.1007/978-3-642-03070-3{\\_}57},\nvolume = {5632 LNAI},\nyear = {2009}\n}\n

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\n \n\n \n \n \n \n \n \n Learning teaching strategies in an Adaptive and Intelligent Educational System through Reinforcement Learning.\n \n \n \n \n\n\n \n Iglesias, A.; Martínez, P.; Aler, R.; and Fernández, F.\n\n\n \n\n\n\n Applied Intelligence, 31(1): 89–106. aug 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Iglesias2009,\nabstract = {One of the most important issues in Adaptive and Intelligent Educational Systems (AIES) is to define effective pedagogical policies for tutoring students according to their needs. This paper proposes to use Reinforcement Learning (RL) in the pedagogical module of an educational system so that the system learns automatically which is the best pedagogical policy for teaching students. One of the main characteristics of this approach is its ability to improve the pedagogical policy based only on acquired experience with other students with similar learning characteristics. In this paper we study the learning performance of the educational system through three important issues. Firstly, the learning convergence towards accurate pedagogical policies. Secondly, the role of exploration/exploitation strategies in the application of RL to AIES. Finally, a method for reducing the training phase of the AIES. {\\textcopyright} 2008 Springer Science+Business Media, LLC.},\nauthor = {Iglesias, Ana and Mart{\\'{i}}nez, Paloma and Aler, Ricardo and Fern{\\'{a}}ndez, Fernando},\ndoi = {10.1007/s10489-008-0115-1},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2Fs10489-008-0115-1.pdf:pdf},\nissn = {0924-669X},\njournal = {Applied Intelligence},\nkeywords = {Adaptive and Intelligent Educational Systems,Applied artificial intelligence,Intelligent tutoring systems,Learning pedagogical strategies,Reinforcement Learning},\nmonth = {aug},\nnumber = {1},\npages = {89--106},\ntitle = {{Learning teaching strategies in an Adaptive and Intelligent Educational System through Reinforcement Learning}},\nurl = {http://link.springer.com/10.1007/s10489-008-0115-1},\nvolume = {31},\nyear = {2009}\n}\n

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\n \n\n \n \n \n \n \n \n Two Steps Reinforcement Learning in Continuous Reinforcement Learning Tasks.\n \n \n \n \n\n\n \n L?pez-Bueno, I.; Garc?a, J.; and Fern?ndez, F.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 5517 LNCS, pages 577–584. 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Two$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{L?pez-Bueno2009,\nabstract = {Two steps reinforcement learning is a technique that combines an iterative refinement of a Q function estimator that can be used to obtains a state space discretization with classical reinforcement learning algorithms like Q-learning or Sarsa. However, the method requires a discrete reward function that permits learning an approximation of the Q function using classification algorithms. However, many domains have continuous reward functions that could only be tackled by discretizing the rewards. In this paper we propose solutions to this problem using discretization and regression methods. We demonstrate the usefulness of the resulting approach to improve the learning process in the Keepaway domain. We compare the obtained results with other techniques like VQQL and CMAC. {\\textcopyright} 2009 Springer Berlin Heidelberg.},\nauthor = {L?pez-Bueno, Iv?n and Garc?a, Javier and Fern?ndez, Fernando},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\ndoi = {10.1007/978-3-642-02478-8_73},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F978-3-642-02478-8{\\_}73.pdf:pdf},\nisbn = {3642024777},\nissn = {03029743},\nnumber = {PART 1},\npages = {577--584},\ntitle = {{Two Steps Reinforcement Learning in Continuous Reinforcement Learning Tasks}},\nurl = {http://link.springer.com/10.1007/978-3-642-02478-8{\\_}73},\nvolume = {5517 LNCS},\nyear = {2009}\n}\n

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\n \n\n \n \n \n \n \n \n Reinforcement learning of pedagogical policies in adaptive and intelligent educational systems.\n \n \n \n \n\n\n \n Iglesias, A.; Mart?nez, P.; Aler, R.; and Fern?ndez, F.\n\n\n \n\n\n\n Knowledge-Based Systems, 22(4): 266–270. may 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Reinforcement$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Iglesias2009a,\nabstract = {In an adaptive and intelligent educational system (AIES), the process of learning pedagogical policies according the students needs fits as a Reinforcement Learning (RL) problem. Previous works have demonstrated that a great amount of experience is needed in order for the system to learn to teach properly, so applying RL to the AIES from scratch is unfeasible. Other works have previously demonstrated in a theoretical way that seeding the AIES with an initial value function learned with simulated students reduce the experience required to learn an accurate pedagogical policy. In this paper we present empirical results demonstrating that a value function learned with simulated students can provide the AIES with a very accurate initial pedagogical policy. The evaluation is based on the interaction of more than 70 Computer Science undergraduate students, and demonstrates that an efficient and useful guide through the contents of the educational system is obtained. {\\textcopyright} 2009 Elsevier B.V. All rights reserved.},\nauthor = {Iglesias, Ana and Mart?nez, Paloma and Aler, Ricardo and Fern?ndez, Fernando},\ndoi = {10.1016/j.knosys.2009.01.007},\nfile = {:home/fernando/papers/tmp/1-s2.0-S0950705109000173-main.pdf:pdf},\nissn = {09507051},\njournal = {Knowledge-Based Systems},\nkeywords = {Adaptive and intelligent educational systems,Artificial intelligence applied to intelligent tut,Distance learning,Reinforcement Learning},\nmonth = {may},\nnumber = {4},\npages = {266--270},\ntitle = {{Reinforcement learning of pedagogical policies in adaptive and intelligent educational systems}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S0950705109000173},\nvolume = {22},\nyear = {2009}\n}\n

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\n \n\n \n \n \n \n \n \n A Unified View of Cost-Based Heuristics.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; and Linares-López, C.\n\n\n \n\n\n\n In , editor(s), Proceedings of Workshop on Heuristics for Domain-Independent Planning, ICAPS'09, Thessaloniki (Greece), September 2009. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{workshop-icaps09-theory,\n\n  author = {Raquel Fuentetaja and Daniel Borrajo and Carlos Linares-López},\n\n  booktitle = {Proceedings of Workshop on Heuristics for Domain-Independent Planning, ICAPS'09},\n\n  title = {A Unified View of Cost-Based Heuristics},\n\n  publisher = {},\n\n  year = {2009},\n\n  key = {Planning-Learning},\n\n  url = {workshop-icaps09-theory.pdf},\n\n  editor = {},\n\n  volume = {},\n\n  series = {},\n\n  address = {Thessaloniki (Greece)},\n\n  month = {September},\n\n  pages = {},\n\n  cicyt = {workshops},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Three Relational Learning Approaches for Lookahead Heuristic Search.\n \n \n \n \n\n\n \n de la Rosa, T.; García-Durán, R.; Jiménez, S.; Fernández, F.; García-Olaya, A.; and Borrajo, D.\n\n\n \n\n\n\n In , editor(s), Proceedings of the Workshop on Planning and Learning of ICAPS09, Thessaloniki (Greece), September 2009. \n \n\n\n\n
\n\n\n\n \n \n $\"Three$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{workshop-learning-icaps09,\n\n  author = {Tomás de la Rosa and Rocío García-Durán and Sergio Jiménez and Fernando Fernández and Angel García-Olaya and Daniel Borrajo},\n\n  booktitle = {Proceedings of the Workshop on Planning and Learning of ICAPS09},\n\n  title = {Three Relational Learning Approaches for Lookahead Heuristic Search},\n\n  publisher = {},\n\n  year = {2009},\n\n  key = {Planning-Learning},\n\n  url = {workshop-learning-icaps09.pdf},\n\n  editor = {},\n\n  volume = {},\n\n  series = {},\n\n  address = {Thessaloniki (Greece)},\n\n  month = {September},\n\n  pages = {},\n\n  cicyt = {workshops},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n OMBO: An opponent modeling approach.\n \n \n \n \n\n\n \n Ledezma, A.; Aler, R.; Sanchis, A.; and Borrajo, D.\n\n\n \n\n\n\n AI Communications, 22(1): 21-35. 2009.\n http://dx.doi.org/10.3233/AIC-2009-0442\n\n\n\n
\n\n\n\n \n \n $\"OMBO:$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aicomm09,\n\n  author = {Agapito Ledezma and Ricardo Aler and Araceli Sanchis and Daniel Borrajo},\n\n  title = {{OMBO: An} opponent modeling approach},\n\n  journal = {AI Communications},\n\n  volume = {22},\n\n  number = {1},\n\n  year = {2009},\n\n  url = {http://hdl.handle.net/10016/6598},\n\n  publisher = {IOS Press},\n\n  address = {},\n\n  key = {Multi-Agent Learning},\n\n  month = {},\n\n  pages = {21-35},\n\n  cicyt = {revista},\n\n  jcr = {Q4, 2009: 0.755 (82/103)},\n\n  optjcr = {2004: 0.738 (42/78), 2005: 0.612 (57/79), 2006: 0.469 (69/85), 2007: 0.585 (68/93)},\n\n  note = {http://dx.doi.org/10.3233/AIC-2009-0442}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Reinforcement Learning of Pedagogical Policies in Adaptive and Intelligent Educational Systems.\n \n \n \n\n\n \n Iglesias, A.; Martínez, P.; Aler, R.; and Fernández, F.\n\n\n \n\n\n\n Knowledge Based Systems, 22(4): 266-270. 2009.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{iglesias09,\n\n  author = {Ana Iglesias and Paloma Martínez and Ricardo Aler and Fernando Fernández},\n\n  title = {Reinforcement Learning of Pedagogical Policies in Adaptive and Intelligent Educational Systems},\n\n  journal = {Knowledge Based Systems},\n\n  key = {Reactive},\n\n  year = {2009},\n\n  volume = {22},\n\n  number = {4},\n\n  pages = {266-270},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Two Steps Reinforcement Learning in Continuous Reinforcement Learning Tasks.\n \n \n \n\n\n \n López-Bueno, I.; García, J.; and Fernández, F.\n\n\n \n\n\n\n In 10th International Work-Conference on Artificial Neural Networks (IWANN 2009), volume 5517, of Lecture Notes in Computer Science, pages 577-584, 2009. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{lopezbueno09,\n\n  author = {Iván López-Bueno and Javier García and Fernando Fernández},\n\n  title = {Two Steps Reinforcement Learning in Continuous Reinforcement Learning Tasks},\n\n  year = {2009},\n\n  booktitle = {10th International Work-Conference on Artificial Neural Networks (IWANN 2009)},\n\n  key = {Reactive},\n\n  volume = {5517},\n\n  series = {Lecture Notes in Computer Science},\n\n  pages = {577-584},\n\n  cicyt = {lncs}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Integrated Planning and Execution for Robotic Exploration.\n \n \n \n\n\n \n McGann, C.; Py, F.; Rajan, K.; and Garcia-Olaya, A.\n\n\n \n\n\n\n In International Workshop on Hybrid Control of Autonomous Systems (HYCAS). International Joint Conferences on Artificial Intelligence (IJCAI), pages 33-40, Pasadena, USA, July 2009. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{McGann09,\n\n  author = {Connor McGann and Frederic Py and Kanna Rajan and Angel Garcia-Olaya},\n\n  title = {Integrated Planning and Execution for Robotic Exploration},\n\n  booktitle = {International Workshop on Hybrid Control of Autonomous Systems (HYCAS). International Joint Conferences on Artificial Intelligence (IJCAI)},\n\n  pages = {33-40},\n\n  year = {2009},\n\n  key = {Planning-Learning},\n\n  address = {Pasadena, USA},\n\n  month = {July},\n\n  cicyt = {workshops}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Learning Teaching Strategies in an Adaptive and Intelligent Educational System through Reinforcement Learning.\n \n \n \n\n\n \n Iglesias, A.; Martínez, P.; Aler, R.; and Fernández, F.\n\n\n \n\n\n\n Applied Intelligence, 31(1): 89-106. 2009.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{iglesias08,\n\n  author = {Ana Iglesias and Paloma Mart\\'inez and Ricardo Aler and Fernando Fern\\'andez},\n\n  title = {Learning Teaching Strategies in an Adaptive and Intelligent Educational System through Reinforcement Learning},\n\n  journal = {Applied Intelligence},\n\n  year = {2009},\n\n  key = {Reactive},\n\n  volume = {31},\n\n  number = {1},\n\n  pages = {89-106},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Improving Automated Planning with Machine Learning.\n \n \n \n\n\n \n Fernández, S.; Jiménez, S.; and de la Rosa, T.\n\n\n \n\n\n\n Handbook of Research on Machine Learning Applications and Trends. E. Soria, J. M.; and A.J.Serrano., editor(s). for publishing, 2009.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inbook{planninglearning08,\n\n  author = {Susana Fernández and Sergio Jiménez and Tomás de la Rosa},\n\n  editor = {E. Soria, J.D. Martín, R. Magdalena, M.Martínez and  A.J.Serrano.},\n\n  title = {Handbook of Research on Machine Learning Applications and Trends},\n\n  optseries = {},\n\n  key = {Planning-Learning},\n\n  chapter = {Improving Automated Planning with Machine Learning},\n\n  publisher = {for publishing},\n\n  year = {2009},\n\n  optpages = {},\n\n  cycit = {capitulos},\n\n  optnote = {ISBN: 978-1-60566-766-9. Publisher:     Information Science Reference}\n\n}\n\n\n\n

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\n \n 2008\n \n \n (23)\n \n \n

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\n \n\n \n \n \n \n \n \n A New Approach to Heuristic Estimations for Cost-Based Planning.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; and Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Twenty-First International FLAIRS Conference, pages 543–548, Coconut Grove, Florida, USA, May 2008. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  fuentetaja.r.borrajo.d.ea:new,\n  author\t= {Raquel Fuentetaja and Daniel Borrajo and Carlos {Linares\n\t\t  L\\'opez}},\n  title\t\t= {A New Approach to Heuristic Estimations for Cost-Based\n\t\t  Planning},\n  booktitle\t= {Proceedings of the Twenty-First International FLAIRS\n\t\t  Conference},\n  pages\t\t= {543--548},\n  year\t\t= {2008},\n  address\t= {Coconut Grove, Florida, USA},\n  month\t\t= may,\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/flairs08-workshop.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Multi-valued Pattern Databases.\n \n \n \n \n\n\n \n Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Eighteenth European Conference on Artificial Intelligence (ECAI'08), pages 540–544, Patras, Greece, July 2008. \n \n\n\n\n
\n\n\n\n \n \n $\"Multi-valued$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c:multi-valued,\n  author\t= {Carlos {Linares L\\'opez}},\n  title\t\t= {Multi-valued Pattern Databases},\n  booktitle\t= {Proceedings of the Eighteenth European Conference on\n\t\t  Artificial Intelligence (ECAI'08)},\n  pages\t\t= {540--544},\n  year\t\t= {2008},\n  address\t= {Patras, Greece},\n  month\t\t= jul,\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/ecai2008.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n The PELA architecture: Integrating planning and learning to improve execution.\n \n \n \n \n\n\n \n Jiménez, S.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the National Conference on Artificial Intelligence (AAAI 2008), volume 3, 2008. \n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Jimenez2008,\nabstract = {Building architectures for autonomous rational behavior requires the integration of several AI components, such as planning, learning and execution monitoring. In most cases, the techniques used for planning and learning are tailored to the specific integrated architecture, so they could not be replaced by other equivalent techniques. Also, in order to solve tasks that require looka-head reasoning under uncertainty, these architectures need an accurate domain model to feed the planning component. But the manual definition of these models is a difficult task. In this paper, we propose an architecture that uses off-the-shelf interchangeable planning and learning components to solve tasks that require flexible planning under uncertainty. We show how a relational learning component can be applied to automatically obtain accurate probabilistic action models from executions of plans. These models can be used by any classical planner that handles metric functions, or, alternatively, by any decision theoretic planner. We also show how these components can be integrated to solve tasks continuously, under an online relational learning scheme. Copyright {\\textcopyright} 2008.},\nauthor = {Jim{\\'{e}}nez, S. and Fern{\\'{a}}ndez, F. and Borrajo, D.},\nbooktitle = {Proceedings of the National Conference on Artificial Intelligence (AAAI 2008)},\nfile = {:home/fernando/papers/tmp/AAAI08-205.pdf:pdf},\nisbn = {9781577353683},\ntitle = {{The PELA architecture: Integrating planning and learning to improve execution}},\nurl = {http://www.aaai.org/Library/AAAI/2008/aaai08-205.php},\nvolume = {3},\nyear = {2008}\n}\n

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\n \n\n \n \n \n \n \n \n Learning and transferring relational instance-based policies.\n \n \n \n \n\n\n \n García-Durán, R.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In AAAI Workshop on Planning and Learning, volume WS-08-13, 2008. \n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Garcia-Duran2008,\nabstract = {A Relational Instance-Based Policy can be defined as an action policy described following a relational instance-based learning approach. The policy is represented with a set of state-goal-action tuples in some form of predicate logic and a distance metric: whenever the planner is in a state trying to reach a goal, the next action to execute is computed as the action associated to the closest state-goal pair in that set. In this work, the representation language is relational, following the ideas of Relational Reinforcement Learning. The policy to transfer (the set of state-goal-action tuples) is generated with a planning system solving optimally simple source problems. The target problems are defined in the same planning domain, have different initial and goal states to the source problems, and could be much more complex. We show that the transferred policy can solve similar problems to the ones used to learn it, but also more complex problems. In fact, the policy learned outperforms the planning system used to generate the initial state-action pairs in two ways: it is faster and scales up better. Copyright {\\textcopyright} 2008, Association for the Advancement of Artificial Intelligence.},\nauthor = {Garc{\\'{i}}a-Dur{\\'{a}}n, R. and Fern{\\'{a}}ndez, F. and Borrajo, D.},\nbooktitle = {AAAI Workshop on Planning and Learning},\nfile = {:home/fernando/papers/tmp/WS08-13-004.pdf:pdf},\ntitle = {{Learning and transferring relational instance-based policies}},\nurl = {http://www.aaai.org/Library/Workshops/2008/ws08-13-004.php},\nvolume = {WS-08-13},\nyear = {2008}\n}\n

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\n \n\n \n \n \n \n \n \n Prototypes Based Relational Learning.\n \n \n \n \n\n\n \n García-Durán, R.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Artificial Intelligence: Methodology, Systems, and Applications, volume 5253 LNAI, pages 130–143. Springer Berlin Heidelberg, Berlin, Heidelberg, 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"Prototypes$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@incollection{Garcia-Duran2008a,\nabstract = {Relational instance-based learning (RIBL) algorithms offer high prediction capabilities. However, they do not scale up well, specially in domains where there is a time bound for classification. Nearest prototype approaches can alleviate this problem, by summarizing the data set in a reduced set of prototypes. In this paper we present an algorithm to build Relational Nearest Prototype Classifiers (rnpc). When compared with RIBL approaches, the algorithm is able to dramatically reduce the number of instances by selecting the most relevant prototypes, maintaining similar accuracy. The number of prototypes is obtained automatically by the algorithm, although it can be also bounded by the user. Empirical results on benchmark data sets demonstrate the utility of this approach compared to other instance based approaches. {\\textcopyright} Springer-Verlag Berlin Heidelberg 2008.},\naddress = {Berlin, Heidelberg},\nauthor = {Garc{\\'{i}}a-Dur{\\'{a}}n, Roc{\\'{i}}o and Fern{\\'{a}}ndez, Fernando and Borrajo, Daniel},\nbooktitle = {Artificial Intelligence: Methodology, Systems, and Applications},\ndoi = {10.1007/978-3-540-85776-1_12},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F978-3-642-02478-8.pdf:pdf},\nisbn = {3540857753},\nissn = {03029743},\nkeywords = {Inductive logic programming,Instance based learning,Nearest prototype},\npages = {130--143},\npublisher = {Springer Berlin Heidelberg},\ntitle = {{Prototypes Based Relational Learning}},\nurl = {http://link.springer.com/10.1007/978-3-540-85776-1{\\_}12},\nvolume = {5253 LNAI},\nyear = {2008}\n}\n

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\n \n\n \n \n \n \n \n \n Nearest prototype classification of noisy data.\n \n \n \n \n\n\n \n Fernández, F.; and Isasi, P.\n\n\n \n\n\n\n Artificial Intelligence Review, 30(1-4): 53–66. dec 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"Nearest$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Fernandez2008,\nabstract = {Nearest prototype approaches offer a common way to design classifiers. However, when data is noisy, the success of this sort of classifiers depends on some parameters that the designer needs to tune, as the number of prototypes. In this work, we have made a study of the ENPC technique, based on the nearest prototype approach, in noisy datasets. Previous experimentation of this algorithm had shown that it does not require any parameter tuning to obtain good solutions in problems where class limits are well defined, and data is not noisy. In this work, we show that the algorithm is able to obtain solutions with high classification success even when data is noisy. A comparison with optimal (hand made) solutions and other different classification algorithms demonstrates the good performance of the ENPC algorithm in accuracy and number of prototypes as the noise level increases. We have performed experiments in four different datasets, each of them with different characteristics. {\\textcopyright} 2009 Springer Science+Business Media B.V.},\nauthor = {Fern{\\'{a}}ndez, Fernando and Isasi, Pedro},\ndoi = {10.1007/s10462-009-9116-7},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2Fs10462-009-9116-7.pdf:pdf},\nissn = {0269-2821},\njournal = {Artificial Intelligence Review},\nkeywords = {Evolutionary learning,Machine learning,Nearest prototype classification},\nmonth = {dec},\nnumber = {1-4},\npages = {53--66},\ntitle = {{Nearest prototype classification of noisy data}},\nurl = {http://link.springer.com/10.1007/s10462-009-9116-7},\nvolume = {30},\nyear = {2008}\n}\n

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\n \n\n \n \n \n \n \n \n Local Feature Weighting in Nearest Prototype Classification.\n \n \n \n \n\n\n \n Fernandez, F.; and Isasi, P.\n\n\n \n\n\n\n IEEE Transactions on Neural Networks, 19(1): 40–53. jan 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"Local$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Fernandez2008a,\nabstract = {The distance metric is the corner stone of nearest neighbor (NN)-based methods, and therefore, of nearest prototype (NP) algorithms. That is because they classify depending on the similarity of the data. When the data is characterized by a set of features which may contribute to the classification task in different levels, feature weighting or selection is required, sometimes in a local sense. However, local weighting is typically restricted to NN approaches. In this paper, we introduce local feature weighting (LFW) in NP classification. LFW provides each prototype its own weight vector, opposite to typical global weighting methods found in the NP literature, where all the prototypes share the same one. Providing each prototype its own weight vector has a novel effect in the borders of the Voronoi regions generated: They become nonlinear. We have integrated LFW with a previously developed evolutionary nearest prototype classifier (ENPC). The experiments performed both in artificial and real data sets demonstrate that the resulting algorithm that we call LFW in nearest prototype classification (LFW-NPC) avoids overfitting on training data in domains where the features may have different contribution to the classification task in different areas of the feature space. This generalization capability is also reflected in automatically obtaining an accurate and reduced set of prototypes. {\\textcopyright} 2007 IEEE.},\nauthor = {Fernandez, F. and Isasi, P.},\ndoi = {10.1109/TNN.2007.902955},\nfile = {:home/fernando/papers/tmp/04359199.pdf:pdf},\nissn = {1045-9227},\njournal = {IEEE Transactions on Neural Networks},\nkeywords = {Evolutionary learning,Local feature weighting (LFW),Nearest prototype (NP) classification,Weighted Euclidean distance},\nmonth = {jan},\nnumber = {1},\npages = {40--53},\ntitle = {{Local Feature Weighting in Nearest Prototype Classification}},\nurl = {http://ieeexplore.ieee.org/document/4359199/},\nvolume = {19},\nyear = {2008}\n}\n

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\n \n\n \n \n \n \n \n \n Two steps reinforcement learning.\n \n \n \n \n\n\n \n Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n International Journal of Intelligent Systems, 23(2): 213–245. feb 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"Two$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Fernandez2008b,\nabstract = {When applying reinforcement learning in domains with very large or continuous state spaces, the experience obtained by the learning agent in the interaction with the environment must be generalized. The generalization methods are usually based on the approximation of the value functions used to compute the action policy and tackled in two different ways. On the one hand by using an approximation of the value functions based on a supervized learning method. On the other hand, by discretizing the environment to use a tabular representation of the value functions. In this work, we propose an algorithm that uses both approaches to use the benefits of both mechanisms, allowing a higher performance. The approach is based on two learning phases. In the first one, a learner is used as a supervized function approximator, but using a machine learning technique which also outputs a state space discretization of the environment, such as nearest prototype classifiers or decision trees do. In the second learning phase, the space discretization computed in the first phase is used to obtain a tabular representation of the value function computed in the previous phase, allowing a tuning of such value function approximation. Experiments in different domains show that executing both learning phases improves the results obtained executing only the first one. The results take into account the resources used and the performance of the learned behavior. {\\textcopyright} 2008 Wiley Periodicals, Inc.},\nauthor = {Fern{\\'{a}}ndez, Fernando and Borrajo, Daniel},\ndoi = {10.1002/int.20255},\nfile = {:home/fernando/papers/tmp/Fern-ndez{\\_}et{\\_}al-2008-International{\\_}Journal{\\_}of{\\_}Intelligent{\\_}Systems.pdf:pdf},\nissn = {08848173},\njournal = {International Journal of Intelligent Systems},\nmonth = {feb},\nnumber = {2},\npages = {213--245},\ntitle = {{Two steps reinforcement learning}},\nurl = {http://doi.wiley.com/10.1002/int.20255},\nvolume = {23},\nyear = {2008}\n}\n

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\n \n\n \n \n \n \n \n \n The PELA architecture: integrating planning and learning to improve execution.\n \n \n \n \n\n\n \n Jiménez, S.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the AAAI'08, Chicago, IL (USA), July 2008. AAAI, AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{aaai08,\n\n  author = {Sergio Jiménez and Fernando Fernández and Daniel Borrajo},\n\n  title = {The {PELA} architecture: integrating planning and learning to improve execution},\n\n  booktitle = {Proceedings of the AAAI'08},\n\n  optcrossref = {},\n\n  key = {Planning-Learning},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  url = {aaai08.pdf},\n\n  year = {2008},\n\n  cicyt = {congresos-buenos},\n\n  organization = {AAAI},\n\n  publisher = {AAAI Press},\n\n  address = {Chicago, IL (USA)},\n\n  month = {July},\n\n  optpages = {},\n\n  note = {},\n\n  optannote = {},\n\n  jcr = {A*}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Learning relational decision trees for guiding heuristic planning.\n \n \n \n \n\n\n \n de la Rosa, T.; Jiménez, S.; and Borrajo, D.\n\n\n \n\n\n\n In , editor(s), Proceedings of ICAPS'08, Sydney (Australia), September 2008. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icaps08-roller,\n\n  author = {Tomás de la Rosa and Sergio Jiménez and Daniel Borrajo},\n\n  booktitle = {Proceedings of ICAPS'08},\n\n  title = {Learning relational decision trees for guiding heuristic planning},\n\n  publisher = {AAAI Press},\n\n  year = {2008},\n\n  key = {Planning-Learning},\n\n  url = {icaps08.pdf},\n\n  editor = {},\n\n  volume = {},\n\n  series = {},\n\n  address = {Sydney (Australia)},\n\n  month = {September},\n\n  pages = {},\n\n  cicyt = {congresos-buenos},\n\n  note = {},\n\n  jcr = {A*}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Modelling a RTS Planning Domain with Cost Conversion and Rewards.\n \n \n \n \n\n\n \n Alcazar, V.; Borrajo, D.; and Linares-López, C.\n\n\n \n\n\n\n In , editor(s), Artificial Intelligence in Games. Workshop of the 18th European Conference on Artificial Intelligence, pages 50–54, Patras (Greece), July 2008. \n \n\n\n\n
\n\n\n\n \n \n $\"Modelling$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{workshop-ecai08,\n\n  author = {Vidal Alcazar and Daniel Borrajo and Carlos Linares-López},\n\n  booktitle = {Artificial Intelligence in Games. Workshop of the 18th European Conference on Artificial Intelligence},\n\n  title = {Modelling a {RTS} Planning Domain with Cost Conversion and Rewards},\n\n  publisher = {},\n\n  url = {workshop-ecai08.pdf},\n\n  year = {2008},\n\n  key = {Planning-Learning},\n\n  url = {},\n\n  month = {July},\n\n  editor = {},\n\n  address = {Patras (Greece)},\n\n  pages = {50--54},\n\n  cicyt = {workshops},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Prototypes Based Relational Learning.\n \n \n \n \n\n\n \n García-Durán, R.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Traverso, P.; and Pistore, M., editor(s), Artificial Intelligence: Methodology, Systems, and Applications, volume 5253/2008, of Lecture Notes in Computer Science, pages 130–143, Varna, Bulgaria, September 2008. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Prototypes$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{aimsa08-rnpc,\n\n  author = {Rocío García-Durán and Fernando Fernández and Daniel Borrajo},\n\n  title = {Prototypes Based Relational Learning},\n\n  booktitle = {Artificial Intelligence: Methodology, Systems, and Applications},\n\n  key = {Planning-Learning},\n\n  url = {aimsa08-rnpc.pdf},\n\n  editor = {Paolo Traverso and Marco Pistore},\n\n  volume = {5253/2008},\n\n  series = {Lecture Notes in Computer Science},\n\n  year = {2008},\n\n  publisher = {Springer Verlag},\n\n  cicyt = {lncs},\n\n  address = {Varna, Bulgaria},\n\n  month = {September},\n\n  pages = {130--143},\n\n  note = {},\n\n  optannote = {31 papers + 13 posters of 109},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Social and Emotional Model for Obtaining Believable Emergent Behavior.\n \n \n \n \n\n\n \n Fernández, S.; Asensio, J.; Jiménez, M.; and Borrajo, D.\n\n\n \n\n\n\n In Traverso, P.; and Pistore, M., editor(s), Artificial Intelligence: Methodology, Systems, and Applications, volume 5253/2008, of Lecture Notes in Computer Science, pages 395–399, Varna, Bulgaria, September 2008. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{aimsa08-alive,\n\n  author = {Susana Fernández and Javier Asensio and Marta Jiménez and Daniel Borrajo},\n\n  title = {A Social and Emotional Model for Obtaining Believable Emergent Behavior},\n\n  booktitle = {Artificial Intelligence: Methodology, Systems, and Applications},\n\n  key = {Other},\n\n  editor = {Paolo Traverso and Marco Pistore},\n\n  url = {http://hdl.handle.net/10016/7728},\n\n  volume = {5253/2008},\n\n  series = {Lecture Notes in Computer Science},\n\n  year = {2008},\n\n  publisher = {Springer Verlag},\n\n  cicyt = {lncs},\n\n  address = {Varna, Bulgaria},\n\n  month = {September},\n\n  pages = {395--399},\n\n  optnote = {http://dx.doi.org/10.1007/978-3-540-85776-1\\_37},\n\n  optannote = {31 papers + 13 posters of 109},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Preference-Oriented Planning for Achieving Satisfactory Emotional States.\n \n \n \n \n\n\n \n Pérez, D.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n In Aylett, R., editor(s), Proceedings of the 27th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG'08), Edinburgh (UK), December 2008. \n \n\n\n\n
\n\n\n\n \n \n $\"Preference-Oriented$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{plansig08,\n\n  author = {Daniel Pérez and Susana Fernández and Daniel Borrajo},\n\n  title = {Preference-Oriented Planning for Achieving Satisfactory Emotional States},\n\n  booktitle = {Proceedings of the 27th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG'08)},\n\n  url = {plansig08.pdf},\n\n  key = {Planning-Learning},\n\n  cicyt = {workshops},\n\n  editor = {Ruth Aylett},\n\n  year = {2008},\n\n  address = {Edinburgh (UK)},\n\n  month = {December},\n\n  pages = {},\n\n  note = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A New Approach to Heuristic Estimations for Cost-Based Planning.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; and Linares-López, C.\n\n\n \n\n\n\n In , editor(s), Proceedings of FLAIRS'08, Coconut Grove, FL (USA), May 2008. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{flairs08,\n\n  author = {Raquel Fuentetaja and Daniel Borrajo and Carlos Linares-López},\n\n  booktitle = {Proceedings of FLAIRS'08},\n\n  title = {A New Approach to Heuristic Estimations for Cost-Based Planning},\n\n  publisher = {},\n\n  year = {2008},\n\n  month = {May},\n\n  key = {Planning-Learning},\n\n  url = {flairs08.pdf},\n\n  editor = {},\n\n  volume = {},\n\n  series = {},\n\n  address = {Coconut Grove, FL (USA)},\n\n  pages = {},\n\n  cicyt = {congresos},\n\n  note = {},\n\n  jcr = {C}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Unsupervised and Domain Independent Ontology Learning. Combining Heterogeneous sources of evidence.\n \n \n \n \n\n\n \n Manzano-Macho, D.; Gómez-Pérez, A.; and Borrajo, D.\n\n\n \n\n\n\n In , editor(s), Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech (Marruecos), June 2008. \n \n\n\n\n
\n\n\n\n \n \n $\"Unsupervised$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{lrec08,\n\n  author = {David Manzano-Macho and Asunción Gómez-Pérez and Daniel Borrajo},\n\n  title = {Unsupervised and Domain Independent Ontology Learning. Combining Heterogeneous sources of evidence},\n\n  booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)},\n\n  key = {Learning-Information Retrieval},\n\n  url = {lrec08.pdf},\n\n  editor = {},\n\n  year = {2008},\n\n  address = {Marrakech (Marruecos)},\n\n  month = {June},\n\n  pages = {},\n\n  cicyt = {congresos},\n\n  annote = {C (CORE 2007)},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n SAMAP. A user-oriented adaptive system for planning tourist visits.\n \n \n \n \n\n\n \n Castillo, L.; Armengol, E.; Onaindía, E.; Sebastiá, L.; González-Boticario, J.; Rodríguez, A.; Fernández, S.; Arias, J. D.; and Borrajo, D.\n\n\n \n\n\n\n Expert Systems with Applications, 34(2): 1318–1332. February 2008.\n ISSN: 0957-4174\n\n\n\n
\n\n\n\n \n \n $\"SAMAP.$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{expertsystems08-samap,\n\n  author = {Luis Castillo and Eva Armengol and Eva Onaindía and Laura\n\n                  Sebastiá and Jesús González-Boticario and Antonio Rodríguez\n\n                  and Susana Fernández and Juan David Arias and Daniel Borrajo},\n\n  title = {{SAMAP}. {A} user-oriented adaptive system for planning tourist visits},\n\n  journal = {Expert Systems with Applications},\n\n  year = {2008},\n\n  publisher = {Elsevier},\n\n  key = {Planning-Learning},\n\n  url = {http://dx.doi.org/10.1016/j.eswa.2006.12.029},\n\n  volume = {34},\n\n  number = {2},\n\n  month = {February},\n\n  pages = {1318--1332},\n\n  cicyt = {revista},\n\n  jcr = {Q1, 2008: 2.596 (17/94), En Categoría Operations Research \\& Management Science: 2008 (1/64)},\n\n  optjcr = {2004: 1.247 (26/78), 2005: 1.236 (32/79), 2006: 0.957 (41/85), 2007: 1.177 (40/93), 2008: 2.596 (17/94)\\\\ En Categoría Operations Research \\& Management Science: 2007 (11/60), 2008 (1/64)},\n\n  note = {ISSN: 0957-4174}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Two Steps Reinforcement Learning.\n \n \n \n \n\n\n \n Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n International Journal of Intelligent Systems, 23(2): 213–245. February 2008.\n http://dx.doi.org/10.1002/int.20255\n\n\n\n
\n\n\n\n \n \n $\"Two$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ijis08,\n\n  author = {Fernando Fernández and Daniel Borrajo},\n\n  title = {Two Steps Reinforcement Learning},\n\n  journal = {International Journal of Intelligent Systems},\n\n  year = {2008},\n\n  key = {Reactive},\n\n  publisher = {Wiley},\n\n  url = {http://hdl.handle.net/10016/6822},\n\n  volume = {23},\n\n  number = {2},\n\n  month = {February},\n\n  pages = {213--245},\n\n  cicyt = {revista},\n\n  jcr = {Q3, 2008: 0.860 (69/94)},\n\n  optjcr = {2004: 0.603 (47/78) 2005: 0.657 (53/79), 2006: 0.429 (70/85), 2007: 0.667 (61/93)},\n\n  note = {http://dx.doi.org/10.1002/int.20255}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Relational Learning Approach to Activity Recognition from Sensor Readings.\n \n \n \n \n\n\n \n Ortiz-Laguna, J.; García-Olaya, A.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the 4th IEEE Intelligent Systems conference (IS'08), Varna (Bulgaria), September 2008. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ieeeis08,\n\n  author = {Javier Ortiz-Laguna and Angel García-Olaya and Daniel Borrajo},\n\n  title = {A Relational Learning Approach to Activity Recognition from Sensor Readings},\n\n  booktitle = {Proceedings of the 4th IEEE Intelligent Systems conference (IS'08)},\n\n  optcrossref = {},\n\n  key = {Planning-Learning},\n\n  url = {ieeeis08.pdf},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  year = {2008},\n\n  cicyt = {congresos},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  address = {Varna (Bulgaria)},\n\n  month = {September},\n\n  optpages = {},\n\n  note = {},\n\n  optannote = {},\n\n  jcr = {C}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Nearest Prototype Classification of Noisy Data.\n \n \n \n\n\n \n Fernández, F.; and Isasi, P.\n\n\n \n\n\n\n Artificial Intelligence Review, 30(1): 53-66. 2008.\n \n\n\n\n
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@article{aireview08,\n\n  author = {Fernando Fernández and Pedro Isasi},\n\n  title = {Nearest Prototype Classification of Noisy Data},\n\n  journal = {Artificial Intelligence Review},\n\n  year = {2008},\n\n  volume = {30},\n\n  number = {1},\n\n  key = {Reactive},\n\n  pages = {53-66},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Multi-valued Pattern Databases.\n \n \n \n\n\n \n Linares, C.\n\n\n \n\n\n\n In Proceedings of the $18^{\\mbox{th}}$ European Conference on Artificial Intelligence (ECAI'08), pages 540–544, Patras, Greece, July 2008. \n \n\n\n\n
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@inproceedings{carlos-ecai08,\n\n  author = {Carlos Linares},\n\n  title = {Multi-valued Pattern Databases},\n\n  booktitle = {Proceedings of the $18^{\\mbox{th}}$ European\n\n                 Conference on Artificial Intelligence (ECAI'08)},\n\n  pages = {540--544},\n\n  year = {2008},\n\n  key = {Search},\n\n  address = {Patras, Greece},\n\n  month = jul,\n\n  cicyt = {congresos-buenos},\n\n  jcr = {(1) A (2) 0.76}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Local Feature Weighting in Nearest Prototype Classification.\n \n \n \n\n\n \n Fernández, F.; and Isasi, P.\n\n\n \n\n\n\n IEEE Transactions on Neural Networks, 19(1): 40-53. 2008.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{fernandez06c,\n\n  author = {Fernando Fernández and Pedro Isasi},\n\n  title = {Local Feature Weighting in Nearest Prototype Classification},\n\n  key = {Reactive},\n\n  journal = {IEEE Transactions on Neural Networks},\n\n  year = {2008},\n\n  volume = {19},\n\n  number = {1},\n\n  pages = {40-53},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Learning based planning.\n \n \n \n\n\n \n Jiménez, S.; and de la Rosa, T.\n\n\n \n\n\n\n Encyclopedia of Artificial Intelligence. Rabuñal, J. R.; Dorado, J.; and Sierra, A. P., editor(s). Information Science Reference, 2008.\n ISBN 978-1-59904-849-9\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inbook{AIencyclopedia08,\n\n  author = {Sergio Jiménez and Tomás de la Rosa},\n\n  editor = {Juan R. Rabuñal and Julian Dorado and Alejandro Pazos Sierra},\n\n  title = {Encyclopedia of Artificial Intelligence},\n\n  chapter = {Learning based planning},\n\n  key = {Planning-Learning},\n\n  publisher = {Information Science Reference},\n\n  year = {2008},\n\n  cycit = {capitulos},\n\n  note = {ISBN 978-1-59904-849-9}\n\n}\n\n\n\n

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\n \n 2007\n \n \n (11)\n \n \n

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\n \n\n \n \n \n \n \n Combining macro-operators with control knowledge.\n \n \n \n\n\n \n García-Duran, R.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n Volume 4455 LNAI 2007.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@book{Garcia-Duran2007,\nabstract = {Inductive Logic Programming (ILP) methods have proven to succesfully acquire knowledge with very different learning paradigms, such as supervised and unsupervised learning or relational reinforcement learning. However, very little has been done on applying it to General Problem Solving (GPS). One of the ILP-based approaches applied to GPS is HAMLET. This method learns control rules (heuristics) for a non linear planner, PRODIGY4.0, which is integrated into the IPSS system; control rules are used as an effective guide when building the planning search tree. Other learning approaches applied to planning generate macro-operators, building high-level blocks of actions, but increasing the branching factor of the search tree. In this paper, we focus on integrating the two different learning approaches (HAMLET and macro-operators learning), to improve a planning process. The goal is to learn control rules that decide when to use the macro-operators. This process is successfully applied in several classical planning domains. {\\textcopyright} Springer-Verlag Berlin Heidelberg 2007.},\nauthor = {Garc{\\'{i}}a-Duran, R. and Fern{\\'{a}}ndez, F. and Borrajo, D.},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\nisbn = {9783540738466},\nissn = {03029743},\ntitle = {{Combining macro-operators with control knowledge}},\nvolume = {4455 LNAI},\nyear = {2007}\n}\n

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\n \n\n \n \n \n \n \n \n Combining Macro-operators with Control Knowledge.\n \n \n \n \n\n\n \n García-Durán, R.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Inductive Logic Programming, volume 4455 LNAI, pages 229–243. Springer Berlin Heidelberg, Berlin, Heidelberg, 2007.\n \n\n\n\n
\n\n\n\n \n \n $\"Combining$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{Garc?a-Dur?n2007,\nabstract = {Inductive Logic Programming (ILP) methods have proven to succesfully acquire knowledge with very different learning paradigms, such as supervised and unsupervised learning or relational reinforcement learning. However, very little has been done on applying it to General Problem Solving (GPS). One of the ILP-based approaches applied to GPS is HAMLET. This method learns control rules (heuristics) for a non linear planner, PRODIGY4.0, which is integrated into the IPSS system; control rules are used as an effective guide when building the planning search tree. Other learning approaches applied to planning generate macro-operators, building high-level blocks of actions, but increasing the branching factor of the search tree. In this paper, we focus on integrating the two different learning approaches (HAMLET and macro-operators learning), to improve a planning process. The goal is to learn control rules that decide when to use the macro-operators. This process is successfully applied in several classical planning domains. {\\textcopyright} Springer-Verlag Berlin Heidelberg 2007.},\naddress = {Berlin, Heidelberg},\nauthor = {Garc{\\'{i}}a-Dur{\\'{a}}n, Roc{\\'{i}}o and Fern{\\'{a}}ndez, Fernando and Borrajo, Daniel},\nbooktitle = {Inductive Logic Programming},\ndoi = {10.1007/978-3-540-73847-3_25},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F978-3-540-73847-3{\\_}25.pdf:pdf},\nisbn = {9783540738466},\nissn = {03029743},\npages = {229--243},\npublisher = {Springer Berlin Heidelberg},\ntitle = {{Combining Macro-operators with Control Knowledge}},\nurl = {http://link.springer.com/10.1007/978-3-540-73847-3{\\_}25},\nvolume = {4455 LNAI},\nyear = {2007}\n}\n

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\n \n\n \n \n \n \n \n \n Transferring Learned Control-Knowledge between Planners.\n \n \n \n \n\n\n \n Fernández, S.; Aler, R.; and Borrajo, D.\n\n\n \n\n\n\n In Veloso, M., editor(s), Proceedings of IJCAI'07, Hyderabad (India), 2007. IJCAI Press\n Poster\n\n\n\n
\n\n\n\n \n \n $\"Transferring$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ijcai07-gebl,\n\n  author = {Susana Fernández and Ricardo Aler and Daniel Borrajo},\n\n  booktitle = {Proceedings of IJCAI'07},\n\n  title = {Transferring Learned Control-Knowledge between Planners},\n\n  publisher = {IJCAI Press},\n\n  year = {2007},\n\n  key = {Planning-Learning},\n\n  url = {http://hdl.handle.net/10016/5686},\n\n  editor = {Manuela Veloso},\n\n  address = {Hyderabad (India)},\n\n  pages = {},\n\n  cicyt = {congresos-buenos},\n\n  note = {Poster},\n\n  jcr = {A*}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Learning action durations from executions.\n \n \n \n \n\n\n \n Lanchas, J.; Jiménez, S.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the ICAPS'07 Workshop on Planning and Learning, Providence, Rhode Island (USA), 2007. \n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{workshop-icaps07,\n\n  author = {Jesús Lanchas and Sergio Jiménez and Fernando Fernández and Daniel Borrajo},\n\n  title = {Learning action durations from executions},\n\n  booktitle = {Proceedings of the ICAPS'07 Workshop on Planning and Learning},\n\n  opteditor = {},\n\n  year = {2007},\n\n  organization = {},\n\n  publisher = {},\n\n  address = {Providence, Rhode Island (USA)},\n\n  month = {},\n\n  key = {Planning-Learning},\n\n  url = {workshop-icaps07.pdf},\n\n  cicyt = {workshops},\n\n  optpages = {},\n\n  note = {},\n\n  optannote = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using Cases Utility for Heuristic Planning Improvement.\n \n \n \n \n\n\n \n De la Rosa, T.; García-Olaya, A.; and Borrajo, D.\n\n\n \n\n\n\n In Weber, R.; and Richter, M., editor(s), Case-Based Reasoning Research and Development: Proceedings of the 7th International Conference on Case-Based Reasoning, volume 4626, of Lecture Notes on Artificial Intelligence, pages 137-148, Belfast, Northern Ireland, UK, August 2007. Springer Verlag\n http://dx.doi.org/10.1007/978-3-540-74141-1_10\n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{iccbr07,\n\n  author = {Tomás {De la Rosa} and Angel García-Olaya and Daniel Borrajo},\n\n  title = {Using Cases Utility for Heuristic Planning Improvement},\n\n  booktitle = {Case-Based Reasoning Research and Development: Proceedings of the 7th International Conference on Case-Based Reasoning},\n\n  month = {August},\n\n  year = {2007},\n\n  publisher = {Springer Verlag},\n\n  pages = {137-148},\n\n  key = {Planning-Learning},\n\n  url = {http://hdl.handle.net/10016/6840},\n\n  editor = {Rosina Weber and Michael Richter},\n\n  address = {Belfast, Northern Ireland, UK},\n\n  isbn = {978-3-540-74138-1},\n\n  volume = {4626},\n\n  cicyt = {lncs},\n\n  series = {Lecture Notes on Artificial Intelligence},\n\n  jcr = {C},\n\n  note = {http://dx.doi.org/10.1007/978-3-540-74141-1\\_10},\n\n  optannote = {era B en 2010}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Case-Based Recommendation of Node Ordering in Planning.\n \n \n \n \n\n\n \n de la Rosa, T.; García-Olaya, A.; and Borrajo, D.\n\n\n \n\n\n\n In II, D. D. D., editor(s), Proceedings of the 20th International FLAIRS Conference, pages 393–398, Key West, FL (USA), May 2007. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Case-Based$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{flairs07-cbr,\n\n  author = {Tomás de la Rosa and Angel García-Olaya and Daniel Borrajo},\n\n  booktitle = {Proceedings of the 20th International FLAIRS Conference},\n\n  title = {Case-Based Recommendation of Node Ordering in Planning},\n\n  publisher = {AAAI Press},\n\n  year = {2007},\n\n  month = {May},\n\n  key = {Planning-Learning},\n\n  url = {flairs07.pdf},\n\n  editor = {Douglas D. Dankel II},\n\n  address = {Key West, FL (USA)},\n\n  pages = {393--398},\n\n  cicyt = {congresos},\n\n  jcr = {C}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n \\sc PLTOOL. A KE Tool for Planning and Learning.\n \n \n \n \n\n\n \n Fernández, S.; Borrajo, D.; Fuentetaja, R.; Arias, J. D.; and Veloso, M.\n\n\n \n\n\n\n Knowledge Engineering Review, 22(2): 153–184. 2007.\n http://dx.doi.org/10.1017/S0269888907001075\n\n\n\n
\n\n\n\n \n \n $\"\\sc$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{kereview07,\n\n  author = {Susana Fernández and Daniel Borrajo and Raquel Fuentetaja and Juan D. Arias and Manuela Veloso},\n\n  title = {{\\sc {PLTOOL}}. {A} {KE} Tool for Planning and Learning},\n\n  journal = {Knowledge Engineering Review},\n\n  year = {2007},\n\n  url = {http://hdl.handle.net/10016/8286},\n\n  key = {Planning-Learning},\n\n  publisher = {Cambridge University Press},\n\n  volume = {22},\n\n  number = {2},\n\n  optmonth = {},\n\n  pages = {153--184},\n\n  cicyt = {revista},\n\n  jcr = {Q2, 2007: 1.312 (35/93)},\n\n  optjcr = {2004: 1.237 (28/78), 2005: 2.179 (16/79), 2006: 0.930 (43/85), 2007: 1.312 (35/93)},\n\n  note = {http://dx.doi.org/10.1017/S0269888907001075},\n\n  annote = {ISSN: 0269-8889}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Integrating Planning and Scheduling in Workflow Domains.\n \n \n \n \n\n\n \n Rodríguez-Moreno, M. D.; Borrajo, D.; Cesta, A.; and Oddi, A.\n\n\n \n\n\n\n Expert Systems with Applications, 33(2): 389–406. October 2007.\n http://dx.doi.org/10.1016/j.eswa.2006.05.027\n\n\n\n
\n\n\n\n \n \n $\"Integrating$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{expertsystems07,\n\n  author = {María Dolores Rodríguez-Moreno and Daniel Borrajo and Amedeo Cesta and Angelo Oddi},\n\n  title = {Integrating Planning and Scheduling in Workflow Domains},\n\n  journal = {Expert Systems with Applications},\n\n  year = {2007},\n\n  publisher = {Elsevier},\n\n  key = {Organisations modelling},\n\n  url = {http://hdl.handle.net/10016/8289},\n\n  volume = {33},\n\n  number = {2},\n\n  month = {October},\n\n  pages = {389--406},\n\n  cicyt = {revista},\n\n  jcr = {Q1, 2007: 1.177 (40/93), En Categoría Operations Research \\& Management Science: 2007 (11/60)},\n\n  optjcr = {2004: 1.247 (26/78), 2005: 1.236 (32/79), 2006: 0.957 (41/85), 2007: 1.177 (40/93), 2008: 2.596 (17/94)\\\\ En Categoría Operations Research \\& Management Science: 2007 (11/60), 2008 (1/64)},\n\n  note = {http://dx.doi.org/10.1016/j.eswa.2006.05.027},\n\n  optannote = {ISSN: 0957-4174}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Learning actions success patterns from execution.\n \n \n \n\n\n \n Jiménez, S.\n\n\n \n\n\n\n In Doctoral Consoritum ICAPS'07, 2007. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{sergio-icaps07,\n\n  author = {Sergio Jiménez},\n\n  title = {Learning actions success patterns from execution},\n\n  key = {Planning-Learning},\n\n  booktitle = {Doctoral Consoritum ICAPS'07},\n\n  cicyt = {congresos},\n\n  year = {2007}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Case-based Search Control for Heuristic Planning.\n \n \n \n\n\n \n De la Rosa, T.\n\n\n \n\n\n\n In ICAPS 2007 Doctoral Consortium, Providence, Rhode Island, USA, September 2007. \n \n\n\n\n
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@inproceedings{DelaRosa_ICAPS07_DC,\n\n  author = {Tomás {De la Rosa}},\n\n  title = {Case-based Search Control for Heuristic Planning},\n\n  booktitle = {ICAPS 2007 Doctoral Consortium},\n\n  month = {September},\n\n  year = {2007},\n\n  key = {Planning-Learning},\n\n  cicyt = {congresos},\n\n  address = {Providence, Rhode Island, USA}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Cognitive Abilities in Agents.\n \n \n \n\n\n \n López, B.; Fernández, S.; Bajo, J.; Corchado, J. M.; Fuentetaja, R.; González, M.; Isern, D.; Jiménez, S.; and Valls, A.\n\n\n \n\n\n\n of Whitestein Series in Software Agent Technologies and Autonomic Computing. Issues in Multi-Agent Systems. The AgentCities.ES Experience. Moreno, A.; and Pavón, J., editor(s). Birkhauser, 2007.\n ISBN 978-3-7643-85-42-2\n\n\n\n
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@inbook{agenticities08,\n\n  author = {Beatriz López and Susana Fernández and Javier Bajo and Juan\n\n                  M. Corchado and Raquel Fuentetaja and Manuel González and\n\n                  David Isern and Sergio Jiménez and Aïda Valls},\n\n  editor = {Antonio Moreno and Juan Pavón},\n\n  title = {Issues in Multi-Agent Systems. The AgentCities.ES Experience},\n\n  series = {Whitestein Series in Software Agent Technologies and Autonomic Computing},\n\n  chapter = {Cognitive Abilities in Agents},\n\n  publisher = {Birkhauser},\n\n  year = {2007},\n\n  key = {Planning-Learning},\n\n  cycit = {capitulos},\n\n  note = {ISBN 978-3-7643-85-42-2}\n\n}\n\n

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\n \n 2006\n \n \n (20)\n \n \n

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\n \n\n \n \n \n \n \n \n Improving Relaxed Planning Graph Heuristics for Metric Optimization.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; and Linares López, C.\n\n\n \n\n\n\n In Proceedings of \"Heuristic Search, Memory Based Heuristics and its Applications\". Workshop of the Twenty-First National Conference on Artificial Intelligence (AAAI'06), pages 79–86, Boston, USA, July 2006. \n \n\n\n\n
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@InProceedings{\t  fuentetaja.r.borrajo.d.ea:improving,\n  author\t= {Raquel Fuentetaja and Daniel Borrajo and Carlos {Linares\n\t\t  L\\'opez}},\n  title\t\t= {Improving Relaxed Planning Graph Heuristics for Metric\n\t\t  Optimization},\n  booktitle\t= {Proceedings of "Heuristic Search, Memory Based Heuristics\n\t\t  and its Applications". Workshop of the Twenty-First\n\t\t  National Conference on Artificial Intelligence (AAAI'06)},\n  pages\t\t= {79--86},\n  month\t\t= jul,\n  year\t\t= {2006},\n  address\t= {Boston, USA},\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/aaai06-workshop.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Heuristic Perimeter Search: First Results.\n \n \n \n \n\n\n \n Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Eleventh Conference of the Spanish Association for Artificial Intelligence (CAEPIA'05), volume 4177, of Lecture Notes in Artificial Intelligence, pages 251–260, Santiago de Compostela, Spain, November 2006. Springer-Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Heuristic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c:heuristic,\n  author\t= {Carlos {Linares L\\'opez}},\n  title\t\t= {Heuristic Perimeter Search: First Results},\n  booktitle\t= {Proceedings of the Eleventh Conference of the Spanish\n\t\t  Association for Artificial Intelligence (CAEPIA'05)},\n  pages\t\t= {251--260},\n  year\t\t= {2006},\n  volume\t= {4177},\n  series\t= {Lecture Notes in Artificial Intelligence},\n  address\t= {Santiago de Compostela, Spain},\n  month\t\t= nov,\n  publisher\t= {Springer-Verlag},\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/caepia05.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Roboskeleton: An architecture for coordinating robot soccer agents.\n \n \n \n \n\n\n \n Camacho, D.; Fernández, F.; and Rodelgo, M. A.\n\n\n \n\n\n\n Engineering Applications of Artificial Intelligence, 19(2): 179–188. mar 2006.\n \n\n\n\n
\n\n\n\n \n \n $\"Roboskeleton:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Camacho2006,\nabstract = {SkeletonAgent is an agent framework whose main feature is to integrate different artificial intelligent skills, like planning or learning, to obtain new behaviours in a multi-agent environment. This framework has been previously instantiated in a deliberative domain (electronic tourism), where planning was used to integrate Web information in a tourist plan. RoboSkeleton results from the instantiation of the same framework, SkeletonAgent, in a very different domain, the robot soccer. This paper shows how this architecture is used to obtain collaborative behaviours in a reactive domain. The paper describes how the different modules of the architecture for the robot soccer agents are designed, directly showing the flexibility of our framework. {\\textcopyright} 2005 Elsevier Ltd. All rights reserved.},\nauthor = {Camacho, David and Fern{\\'{a}}ndez, Fernando and Rodelgo, Miguel A.},\ndoi = {10.1016/j.engappai.2005.07.002},\nfile = {:home/fernando/papers/tmp/1-s2.0-S0952197605000874-main.pdf:pdf},\nissn = {09521976},\njournal = {Engineering Applications of Artificial Intelligence},\nkeywords = {Distributed AI systems,Multi-agent architectures,Robot soccer},\nmonth = {mar},\nnumber = {2},\npages = {179--188},\ntitle = {{Roboskeleton: An architecture for coordinating robot soccer agents}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S0952197605000874},\nvolume = {19},\nyear = {2006}\n}\n

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\n \n\n \n \n \n \n \n \n Probabilistic policy reuse in a reinforcement learning agent.\n \n \n \n \n\n\n \n Fernández, F.; and Veloso, M.\n\n\n \n\n\n\n In Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems - AAMAS '06, volume 2006, pages 720, New York, New York, USA, 2006. ACM Press\n \n\n\n\n
\n\n\n\n \n \n $\"Probabilistic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Fernandez2006,\nabstract = {We contribute Policy Reuse as a technique to improve a re-inforcement learning agent with guidance from past learned similar policies. Our method relies on using the past policies as a probabilistic bias where the learning agent faces three choices: the exploitation of the ongoing learned policy, the exploration of random unexplored actions, and the exploitation of past policies. We introduce the algorithm and its major components: an exploration strategy to include the new reuse bias, and a similarity function to estimate the similarity of past policies with respect to a new one. We provide empirical results demonstrating that Policy Reuse improves the learning performance over different strategies that learn without reuse. Interestingly and almost as a side effect, Policy Reuse also identifies classes of similar policies revealing a basis of core policies of the domain. We demonstrate that such a basis can be built incrementally, contributing the learning of the structure of a domain. Copyright 2006 ACM.},\naddress = {New York, New York, USA},\nauthor = {Fern{\\'{a}}ndez, Fernando and Veloso, Manuela},\nbooktitle = {Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems - AAMAS '06},\ndoi = {10.1145/1160633.1160762},\nfile = {:home/fernando/papers/tmp/p720-fernandez.pdf:pdf},\nisbn = {1595933034},\npages = {720},\npublisher = {ACM Press},\ntitle = {{Probabilistic policy reuse in a reinforcement learning agent}},\nurl = {http://portal.acm.org/citation.cfm?doid=1160633.1160762},\nvolume = {2006},\nyear = {2006}\n}\n

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\n \n\n \n \n \n \n \n Reusing and building a policy library.\n \n \n \n\n\n \n Fernández, F.; and Veloso, M.\n\n\n \n\n\n\n In ICAPS 2006 - Proceedings, Sixteenth International Conference on Automated Planning and Scheduling, volume 2006, 2006. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{Fernandez2006a,\nabstract = {Policy Reuse is a method to improve reinforcement learning with the ability to solve multiple tasks by building upon past problem solving experience, as accumulated in a Policy Library. Given a new task, a Policy Reuse learner uses the past policies in the library as a probabilistic bias in its new learning process. We present how the effectiveness of each reuse episode is indicative of the novelty of the new task with respect to the previously solved ones in the policy library. In the paper we review Policy Reuse, and we introduce theoretical results that demonstrate that: (i) a Policy Library can be selectively and incrementally built while learning different problems; (ii) the Policy Library can be understood as a basis of the domain that represents its structure through a set of core policies; and (iii) given the basis of a domain, we can define a lower bound for its reuse gain. Copyright {\\textcopyright} 2006, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.},\nauthor = {Fern{\\'{a}}ndez, F. and Veloso, M.},\nbooktitle = {ICAPS 2006 - Proceedings, Sixteenth International Conference on Automated Planning and Scheduling},\nfile = {:home/fernando/papers/tmp/5e09b9317338dab655305490e5d12c92e33c.pdf:pdf},\ntitle = {{Reusing and building a policy library}},\nvolume = {2006},\nyear = {2006}\n}\n

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\n \n\n \n \n \n \n \n \n Nearest Prototype Classification for Relational Learning.\n \n \n \n \n\n\n \n García, R.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Muggleton, S.; and Otero, R., editor(s), Proceedings of International Conference on Inductive Logic Programming (ILP'06), pages 89–91, Santiago de Compostela (Spain), 2006. Universidad of Coruña\n \n\n\n\n
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@inproceedings{ilp06-rnpc,\n\n  author = {Rocío García and Fernando Fernández and Daniel Borrajo},\n\n  booktitle = {Proceedings of International Conference on Inductive Logic\n\n                  Programming (ILP'06)},\n\n  title = {Nearest Prototype Classification for Relational Learning},\n\n  publisher = {Universidad of Coruña},\n\n  url = {ilp06-rnpc.pdf},\n\n  year = {2006},\n\n  key = {Planning-Learning},\n\n  url = {},\n\n  editor = {Stephen Muggleton and Ramón Otero},\n\n  address = {Santiago de Compostela (Spain)},\n\n  cicyt = {congresos},\n\n  pages = {89--91},\n\n  note = {},\n\n  jcr = {B}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Combining Macro-operators with Control Knowledge.\n \n \n \n \n\n\n \n García, R.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Otero, R., editor(s), Proceedings of International Conference on Inductive Logic Programming (ILP'06), volume 4455, of Lecture Notes on Artificial Intelligence, pages 229–243, Santiago de Compostela (Spain), 2006. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Combining$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ilp06-macros-lnai,\n\n  author = {Rocío García and Fernando Fernández and Daniel Borrajo},\n\n  booktitle = {Proceedings of  International Conference on Inductive Logic\n\n                  Programming (ILP'06)},\n\n  title = {Combining Macro-operators with Control Knowledge},\n\n  publisher = {Springer Verlag},\n\n  year = {2006},\n\n  key = {Planning-Learning},\n\n  url = {ilp06-macros-lnai.pdf},\n\n  editor = {Ramón Otero},\n\n  volume = {4455},\n\n  series = {Lecture Notes on Artificial Intelligence},\n\n  address = {Santiago de Compostela (Spain)},\n\n  cicyt = {lncs},\n\n  pages = {229--243},\n\n  note = {},\n\n  annote = {ISBN: },\n\n  jcr = {B}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n HOLA: A Hibrid Ontology Learning Architecture.\n \n \n \n \n\n\n \n Manzano-Macho, D.; Gómez-Pérez, A.; and Borrajo, D.\n\n\n \n\n\n\n In Staab, S.; and Svatek, V., editor(s), Proceedings of the 15th International Conference on Knowledge Engineering and Knowledge Management (EKAW2006), Podebrady (Czech Republic), October 2006. \n Poster\n\n\n\n
\n\n\n\n \n \n $\"HOLA:$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ekaw06,\n\n  author = {David Manzano-Macho and Asunción Gómez-Pérez and Daniel Borrajo},\n\n  title = {{HOLA: A} Hibrid Ontology Learning Architecture},\n\n  booktitle = {Proceedings of the 15th International Conference on\n\n                  Knowledge Engineering and Knowledge Management (EKAW2006)},\n\n  key = {Learning-Information Retrieval},\n\n  url = {ekaw06.pdf},\n\n  editor = {Steffen Staab and Vojtech Svatek},\n\n  year = {2006},\n\n  address = {Podebrady (Czech Republic)},\n\n  month = {October},\n\n  pages = {},\n\n  cicyt = {congresos},\n\n  note = {Poster},\n\n  jcr = {B}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Improving control-knowledge acquisition for planning by active learning.\n \n \n \n \n\n\n \n Fuentetaja, R.; and Borrajo, D.\n\n\n \n\n\n\n In Tobias Scheffer, J. F.; and Spiliopoulou, M., editor(s), Proceedings of 17th European Conference on Machine Learning (ECML'06), volume 4212, of Lecture Notes in Computer Science, pages 138–149, Berlin (Germany), 2006. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Improving$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ecml06,\n\n  author = {Raquel Fuentetaja and Daniel Borrajo},\n\n  booktitle = {Proceedings of 17th {European Conference on Machine Learning (ECML'06)}},\n\n  title = {Improving control-knowledge acquisition for planning by active learning},\n\n  publisher = {Springer Verlag},\n\n  year = {2006},\n\n  key = {Planning-Learning},\n\n  url = {ecml06.pdf},\n\n  editor = {Tobias Scheffer, Johannes Fuernkranz and Myra Spiliopoulou},\n\n  volume = {4212},\n\n  series = {Lecture Notes in Computer Science},\n\n  cicyt = {congresos-buenos},\n\n  address = {Berlin (Germany)},\n\n  pages = {138--149},\n\n  note = {},\n\n  annote = {ISBN: 978-3-540-45375-8},\n\n  jcr = {A}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Improving relaxed planning graph heuristics for metric optimization.\n \n \n \n \n\n\n \n Fuentetaja, R.; Borrajo, D.; and Linares-López, C.\n\n\n \n\n\n\n In Felner, A.; Holte, R. C.; and Geffner, H., editor(s), Working notes of the AAAI'06 Workshop on Heuristic Search, Memory Based Heuristics and Their Applications, Boston, MA (USA), July 2006. AAAI Press\n \n\n\n\n
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@inproceedings{aaai06-workshop-heuristic-costs,\n\n  author = {Raquel Fuentetaja and Daniel Borrajo and Carlos Linares-López},\n\n  title = {Improving relaxed planning graph heuristics for metric optimization},\n\n  booktitle = {Working notes of the {AAAI'06} Workshop on Heuristic Search,\n\n                  Memory Based Heuristics and Their Applications},\n\n  key = {Planning-Learning},\n\n  editor = {Ariel Felner and Robert C. Holte and Hector Geffner},\n\n  year = {2006},\n\n  address = {Boston, MA (USA)},\n\n  publisher = {AAAI Press},\n\n  cicyt = {workshops},\n\n  url = {aaai06-workshop-heuristic-costs.pdf},\n\n  month = {July},\n\n  pages = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Inducing non-deterministic actions behavior to plan robustly in non-deterministic domains.\n \n \n \n \n\n\n \n Jiménez, S.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Guettier, C., editor(s), Working notes of the ICAPS'06 Workshop on Planning under Uncertainty and Execution Control for Autonomous Systems, pages 67–74, Ambleside (U.K.), June 2006. \n \n\n\n\n
\n\n\n\n \n \n $\"Inducing$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icaps06-workshop-luck,\n\n  author = {Sergio Jiménez and Fernando Fernández and Daniel Borrajo},\n\n  title = {Inducing non-deterministic actions behavior to plan robustly\n\n                  in non-deterministic domains},\n\n  booktitle = {Working notes of the {ICAPS'06} Workshop on Planning under\n\n                  Uncertainty and Execution Control for Autonomous Systems},\n\n  key = {Planning-Learning},\n\n  cicyt = {workshops},\n\n  url = {icaps06-workshop-luck.pdf},\n\n  editor = {Christophe Guettier},\n\n  year = {2006},\n\n  address = {Ambleside (U.K.)},\n\n  month = {June},\n\n  pages = {67--74},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Planning for an AI based virtual agents game.\n \n \n \n \n\n\n \n Fernández, S.; Adarve, R.; Pérez, M.; Rybarczyk, M.; and Borrajo, D.\n\n\n \n\n\n\n In Aylett, R.; and Young, M., editor(s), Working notes of the ICAPS'06 Workshop on AI Planning for Computer Games and Synthetic Characters, pages 14–20, Ambleside (U.K.), June 2006. \n \n\n\n\n
\n\n\n\n \n \n $\"Planning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icaps06-workshop-sims,\n\n  author = {Susana Fernández and Roberto Adarve and Miguel Pérez and\n\n                  Martín Rybarczyk and Daniel Borrajo},\n\n  title = {Planning for an {AI} based virtual agents game},\n\n  booktitle = {Working notes of the {ICAPS'06} Workshop on AI Planning for\n\n                  Computer Games and Synthetic Characters},\n\n  key = {Other},\n\n  editor = {Ruth Aylett and Michael Young},\n\n  cicyt = {workshops},\n\n  url = {icaps06-workshop-sims.pdf},\n\n  year = {2006},\n\n  address = {Ambleside (U.K.)},\n\n  month = {June},\n\n  pages = {14--20},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Learning by Knowledge Sharing in Autonomous Intelligent Systems.\n \n \n \n \n\n\n \n García-Martínez, R.; Borrajo, D.; Maceri, P.; and Britos, P.\n\n\n \n\n\n\n In , editor(s), Advances in Artificial Intelligence - IBERAMIA-SBIA 2006, volume 4140, of Lecture Notes in Computer Science, pages 128-137, Berlin (Germany), 2006. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{iberamia06,\n\n  author = {Ramón García-Martínez and Daniel Borrajo and Pablo Maceri and Paola Britos},\n\n  booktitle = {Advances in Artificial Intelligence - IBERAMIA-SBIA 2006},\n\n  title = {Learning by Knowledge Sharing in Autonomous Intelligent Systems},\n\n  publisher = {Springer Verlag},\n\n  year = {2006},\n\n  key = {Reactive},\n\n  url = {iberamia06.pdf},\n\n  editor = {},\n\n  volume = {4140},\n\n  series = {Lecture Notes in Computer Science},\n\n  cicyt = {lncs},\n\n  address = {Berlin (Germany)},\n\n  pages = {128-137},\n\n  note = {},\n\n  annote = {ISSN 0302-9743 (Print) 1611-3349 (Online) ISBN 978-3-540-45462-5},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n IPSS: A Hybrid Approach to Planning and Scheduling Integration.\n \n \n \n \n\n\n \n Rodríguez-Moreno, M. D.; Oddi, A.; Borrajo, D.; and Cesta, A.\n\n\n \n\n\n\n IEEE Transactions on Knowledge and Data Engineering, 18(12): 1681-1695. December 2006.\n http://dx.doi.org/10.1109/TKDE.2006.191\n\n\n\n
\n\n\n\n \n \n $\"IPSS:$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ieeetkde06,\n\n  author = {María Dolores Rodríguez-Moreno and Angelo Oddi and Daniel Borrajo and Amedeo Cesta},\n\n  title = {{IPSS}: {A} Hybrid Approach to Planning and Scheduling Integration},\n\n  journal = {IEEE Transactions on Knowledge and Data Engineering},\n\n  year = {2006},\n\n  url = {http://hdl.handle.net/10016/6797},\n\n  key = {Planning-Learning},\n\n  publisher = {IEEE Press},\n\n  volume = {18},\n\n  number = {12},\n\n  month = {December},\n\n  pages = {1681-1695},\n\n  cicyt = {revista},\n\n  jcr = {Q1, 2006: 2.063 (15/85)},\n\n  optjcr = {2004: 1.243 (27/78), 2005: 1.758 (24/79), 2006: 2.063 (15/85), 2007: 1.896 (20/93).\\\\ En Categoría\n\n                  Computer Science, Information Systems: 2006 (13/87), 2007 (15/92)},\n\n  annote = {ISSN: 1041-4347},\n\n  note = {http://dx.doi.org/10.1109/TKDE.2006.191}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Multi-agent plan based information gathering.\n \n \n \n \n\n\n \n Camacho, D.; Aler, R.; Borrajo, D.; and Molina, J. M.\n\n\n \n\n\n\n Applied Intelligence, 25(1): 59–71. August 2006.\n http://dx.doi.org/10.1007/s10489-006-8866-z\n\n\n\n
\n\n\n\n \n \n $\"Multi-agent$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{applied06,\n\n  author = {David Camacho and Ricardo Aler and Daniel Borrajo and José M. Molina},\n\n  title = {Multi-agent plan based information gathering},\n\n  journal = {Applied Intelligence},\n\n  year = {2006},\n\n  key = {Planning-Web},\n\n  volume = {25},\n\n  number = {1},\n\n  url = {http://hdl.handle.net/10016/5865},\n\n  cicyt = {revista},\n\n  month = {August},\n\n  pages = {59--71},\n\n  publisher = {Springer Verlag},\n\n  jcr = {Q4, 2006: 0.329 (76/85)},\n\n  optjcr = {2004: 0.477 (60/78), 2005: 0.569 (58/79), 2006: 0.329 (76/85), 2007: 0.500 (72/93)},\n\n  note = {http://dx.doi.org/10.1007/s10489-006-8866-z},\n\n  optannote = {ISSN 0924-669X (Print) 1573-7497 (Online)}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Heuristic Perimeter Search: First Results.\n \n \n \n\n\n \n Linares, C.\n\n\n \n\n\n\n In Marín, R.; Onaindía, E.; Bugarín, A.; and Santos, J., editor(s), volume 4177, pages 251–260, Santiago de Compostela (Spain), November 2006. Springer-Verlag\n Proceedings of the XI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA'05)\n\n\n\n
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@inproceedings{linares.c:heuristic,\n\n  author = {Carlos Linares},\n\n  title = {Heuristic Perimeter Search: First Results},\n\n  journal = {Lecture Notes in Artificial Intelligence},\n\n  year = {2006},\n\n  volume = {4177},\n\n  pages = {251--260},\n\n  cicyt = {lncs},\n\n  key = {Search},\n\n  note = {Proceedings of the XI Conferencia de la Asociaci\\'on\n\n         Espa\\~nola para la Inteligencia Artificial (CAEPIA'05)},\n\n  editor = {Roque Mar\\'{\\i}n and Eva Onaind\\'{\\i}a and Alberto Bugar\\'{\\i}n and Jos\\'e Santos},\n\n  address = {Santiago de Compostela (Spain)},\n\n  month = nov,\n\n  publisher = {Springer-Verlag}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Roboskeleton: An Architecture for Coordinating Robot Soccer Agents.\n \n \n \n\n\n \n Camacho, D.; Fernández, F.; and Rodelgo, M. Á.\n\n\n \n\n\n\n Engineering Applications of Artificial Intelligence, 19(2): 179-188. 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{camacho05,\n\n  author = {David Camacho and Fernando Fernández and Miguel \\'Angel Rodelgo},\n\n  title = {Roboskeleton: An Architecture for Coordinating Robot Soccer Agents},\n\n  key = {Multi-Agent Learning},\n\n  journal = {Engineering Applications of Artificial Intelligence},\n\n  volume = {19},\n\n  number = {2},\n\n  pages = {179-188},\n\n  cicyt = {revista},\n\n  year = {2006}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Probabilistic Policy Reuse in a Reinforcement Learning Agent.\n \n \n \n\n\n \n Fernández, F.; and Veloso, M.\n\n\n \n\n\n\n In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS'06), 2006. \n \n\n\n\n
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@inproceedings{fernandez06a,\n\n  author = {Fernando Fern\\'andez and Manuela Veloso},\n\n  title = {Probabilistic Policy Reuse in a Reinforcement Learning Agent},\n\n  key = {Reactive},\n\n  booktitle = {Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS'06)},\n\n  cicyt = {congresos-buenos},\n\n  optpages = {},\n\n  year = {2006}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Reusing and Building Policy Libraries.\n \n \n \n\n\n \n Fernández, F.; and Veloso, M.\n\n\n \n\n\n\n In Proceedings of the International Conference on Automated Planning and Schedulling (ICAPS'06), 2006. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{fernandez06b,\n\n  author = {Fernando Fern\\'andez and Manuela Veloso},\n\n  title = {Reusing and Building Policy Libraries},\n\n  key = {Reactive},\n\n  booktitle = {Proceedings of the International Conference on Automated Planning and Schedulling (ICAPS'06)},\n\n  cicyt = {congresos-buenos},\n\n  optpages = {},\n\n  year = {2006}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n A Mobile Telemedicine Workspace for Diabetes Management.\n \n \n \n\n\n \n Hernando, M. E.; Gómez, E. J.; García-Olaya, A.; Torralba, V.; and del Pozo, F.\n\n\n \n\n\n\n M- Health: Emerging Mobile Health Systems, pages 587-600. R. Istepanian, S. L.; and Pattichis, C., editor(s). Editorial Springer ISBN: 0-387-26558-9, 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inbook{Hernando06,\n\n  author = {M. Elena Hernando and Enrique J. Gómez and Angel García-Olaya and Verónica Torralba and Francisco del Pozo},\n\n  title = {M- Health: Emerging Mobile Health Systems},\n\n  year = {2006},\n\n  pages = {587-600},\n\n  publisher = {Editorial Springer   ISBN: 0-387-26558-9},\n\n  editor = {R. Istepanian, S. Laxminarayan and C. Pattichis},\n\n  chapter = {A Mobile Telemedicine Workspace for Diabetes Management},\n\n  key = {Other},\n\n  cicyt = {capitulos}\n\n}\n\n\n\n

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\n \n 2005\n \n \n (13)\n \n \n

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\n \n\n \n \n \n \n \n \n Machine Learning of Plan Robustness Knowledge About Instances.\n \n \n \n \n\n\n \n Jiménez, S.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 3720 LNAI, pages 609–616. 2005.\n \n\n\n\n
\n\n\n\n \n \n $\"Machine$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{Jimenez2005,\nabstract = {Classical planning domain representations assume all the objects from one type are exactly the same. But when solving problems in the real world systems, the execution of a plan that theoretically solves a problem, can fail because of not properly capturing the special features of an object in the initial representation. We propose to capture this uncertainty about the world with an architecture that integrates planning, execution and learning. In this paper, we describe the PELA system (Planning-Execution-Learning Architecture). This system generates plans, executes those plans in the real world, and automatically acquires knowledge about the behaviour of the objects to strengthen the execution processes in the future. {\\textcopyright} Springer-Verlag Berlin Heidelberg 2005.},\nauthor = {Jim{\\'{e}}nez, Sergio and Fern{\\'{a}}ndez, Fernando and Borrajo, Daniel},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\ndoi = {10.1007/11564096_60},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F11564096{\\_}60.pdf:pdf},\nisbn = {3540292438},\nissn = {03029743},\npages = {609--616},\ntitle = {{Machine Learning of Plan Robustness Knowledge About Instances}},\nurl = {http://link.springer.com/10.1007/11564096{\\_}60},\nvolume = {3720 LNAI},\nyear = {2005}\n}\n

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\n \n\n \n \n \n \n \n \n A Reinforcement Learning Algorithm in Cooperative Multi-Robot Domains.\n \n \n \n \n\n\n \n Fernández, F.; Borrajo, D.; and Parker, L. E.\n\n\n \n\n\n\n Journal of Intelligent and Robotic Systems, 43(2-4): 161–174. dec 2005.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Fernandez2005,\nabstract = {Reinforcement learning has been widely applied to solve a diverse set of learning tasks, from board games to robot behaviours. In some of them, results have been very successful, but some tasks present several characteristics that make the application of reinforcement learning harder to define. One of these areas is multi-robot learning, which has two important problems. The first is credit assignment, or how to define the reinforcement signal to each robot belonging to a cooperative team depending on the results achieved by the whole team. The second one is working with large domains, where the amount of data can be large and different in each moment of a learning step. This paper studies both issues in a multi-robot environment, showing that introducing domain knowledge and machine learning algorithms can be combined to achieve successful cooperative behaviours. {\\textcopyright} Springer 2005.},\nauthor = {Fern{\\'{a}}ndez, Fernando and Borrajo, Daniel and Parker, Lynne E.},\ndoi = {10.1007/s10846-005-5137-x},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2Fs10846-005-5137-x.pdf:pdf},\nissn = {0921-0296},\njournal = {Journal of Intelligent and Robotic Systems},\nkeywords = {Collaborative multi-robot domains,Function approximation,Reinforcement learning,State space discretizations},\nmonth = {dec},\nnumber = {2-4},\npages = {161--174},\ntitle = {{A Reinforcement Learning Algorithm in Cooperative Multi-Robot Domains}},\nurl = {http://link.springer.com/10.1007/s10846-005-5137-x},\nvolume = {43},\nyear = {2005}\n}\n

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\n \n\n \n \n \n \n \n \n Machine learning of plan robustness knowledge about instances.\n \n \n \n \n\n\n \n Jiménez, S.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Gama, J.; Camacho, R.; Brazdil, P. B.; Jorge, A. M.; and Torgo, L., editor(s), Proceedings of 16th European Conference on Machine Learning (ECML'05), volume 3720, of Lecture Notes in Computer Science, pages 609–616, Porto (Portugal), 2005. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Machine$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ecml05,\n\n  author = {Sergio Jiménez and Fernando Fernández and Daniel Borrajo},\n\n  booktitle = {Proceedings of 16th {European Conference on Machine Learning (ECML'05)}},\n\n  title = {Machine learning of plan robustness knowledge about instances},\n\n  publisher = {Springer Verlag},\n\n  year = {2005},\n\n  key = {Planning-Learning},\n\n  url = {ecml05.pdf},\n\n  editor = {João Gama and Rui Camacho and Pavel B. Brazdil and Alípio\n\n                  M. Jorge and Luís Torgo},\n\n  volume = {3720},\n\n  series = {Lecture Notes in Computer Science},\n\n  cicyt = {congresos-buenos},\n\n  address = {Porto (Portugal)},\n\n  pages = {609--616},\n\n  jcr = {A}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Capturing knowledge about the instances behavior in probabilistic domains.\n \n \n \n \n\n\n \n Jiménez, S.; Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In Tucson, A., editor(s), Proceedings of the 24th Workshop of the UK Planning and Scheduling Special Interest Group, pages 44–51, London (UK), December 2005. \n \n\n\n\n
\n\n\n\n \n \n $\"Capturing$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{plansig05,\n\n  author = {Sergio Jiménez and Fernando Fernández and Daniel Borrajo},\n\n  title = {Capturing knowledge about the instances behavior in\n\n                  probabilistic domains},\n\n  booktitle = {Proceedings of the 24th Workshop of the UK Planning and\n\n                  Scheduling Special Interest Group},\n\n  url = {plansig05.pdf},\n\n  key = {Planning-Learning},\n\n  cicyt = {workshops},\n\n  editor = {Andrew Tucson},\n\n  year = {2005},\n\n  address = {London (UK)},\n\n  month = {December},\n\n  pages = {44--51},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Tool for automatically acquiring control knowledge for planning.\n \n \n \n \n\n\n \n Borrajo, D.; Fernández, S.; Fuentetaja, R.; Arias, J. D.; and Veloso, M.\n\n\n \n\n\n\n In Barták, R.; and McCluskey, L., editor(s), Working notes of the ICAPS'05 Competition on Knowledge Engineering for Planning and Scheduling, pages 11-17, Monterey, CA (USA), June 2005. AAAI, AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Tool$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icaps05-icke,\n\n  author = {Daniel Borrajo and Susana Fernández and Raquel Fuentetaja and Juan David Arias and Manuela Veloso},\n\n  title = {Tool for automatically acquiring control knowledge for planning},\n\n  booktitle = {Working notes of the ICAPS'05 Competition on Knowledge\n\n                  Engineering for Planning and Scheduling},\n\n  key = {Planning-Learning},\n\n  editor = {Roman Barták and Lee McCluskey},\n\n  url = {icaps05-icke.pdf},\n\n  cicyt = {otras-publicaciones},\n\n  year = {2005},\n\n  organization = {AAAI},\n\n  publisher = {AAAI Press},\n\n  address = {Monterey, CA (USA)},\n\n  month = {June},\n\n  pages = {11-17},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Automatic Generation of Literary Texts: Greek Mythology.\n \n \n \n \n\n\n \n Fernández, S.; Pérez, D.; and Borrajo, D.\n\n\n \n\n\n\n In Pablo Gervás, T. V.; and Pease, A., editor(s), Working notes of the IJCAI'05 Workshop on Computational Creativity, pages 3–9, Edinburgh (Scotland), August 2005. IJCAI\n \n\n\n\n
\n\n\n\n \n \n $\"Automatic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ijcai05-workshop,\n\n  author = {Susana Fernández and Daniel Pérez and Daniel Borrajo},\n\n  title = {Automatic Generation of Literary Texts: {G}reek Mythology},\n\n  booktitle = {Working notes of the IJCAI'05 Workshop on Computational Creativity},\n\n  key = {Other},\n\n  editor = {Pablo Gervás, Tony Veale and Alison Pease},\n\n  year = {2005},\n\n  organization = {IJCAI},\n\n  publisher = {},\n\n  cicyt = {workshops},\n\n  url = {ijcai05-workshop.pdf},\n\n  address = {Edinburgh (Scotland)},\n\n  month = {August},\n\n  pages = {3--9},\n\n  annote = {Also as Technical Report 5-05, Dep. de Sistemas Informáticos\n\n                  y Programación, Univ. Complutense de Madrid},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using ontologies for planning tourist visits.\n \n \n \n \n\n\n \n Arias, J. D.; Sebastiá, L.; and Borrajo, D.\n\n\n \n\n\n\n In Working notes of the ICAPS'05 Workshop on Role of Ontologies in Planning and Scheduling, pages 52–59, Monterey, CA (EEUU), June 2005. AAAI, AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icaps05-ontologies-workshop,\n\n  author = {Juan David Arias and Laura Sebastiá and Daniel Borrajo},\n\n  title = {Using ontologies for planning tourist visits},\n\n  booktitle = {Working notes of the ICAPS'05 Workshop on Role of Ontologies in Planning and Scheduling},\n\n  key = {Planning-Learning},\n\n  opteditor = {},\n\n  url = {icaps05-ontologies-workshop.pdf},\n\n  year = {2005},\n\n  organization = {AAAI},\n\n  cicyt = {workshops},\n\n  publisher = {AAAI Press},\n\n  address = {Monterey, CA (EEUU)},\n\n  month = {June},\n\n  pages = {52--59},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Computer emulation of Boole's Discovery.\n \n \n \n\n\n \n Ledesma, L.; Pérez, A.; Borrajo, D.; and Laita, L. M.\n\n\n \n\n\n\n of Memorias de la Real Academia de Ciencias, XXXIII. The Genesis of Boole's logic: its History and a Computer Exploration, pages 95–118. Luis M. Laita, L. d. L., editor(s). Real Academia de Ciencias, Madrid, 2005.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inbook{chapter-boole,\n\n  author = {Luis Ledesma and Aurora Pérez and Daniel Borrajo and Luis\n\n                  M. Laita},\n\n  title = {The Genesis of {B}oole's logic: its History and a Computer Exploration},\n\n  chapter = {Computer emulation of {B}oole's Discovery},\n\n  publisher = {Real Academia de Ciencias},\n\n  year = {2005},\n\n  key = {Other},\n\n  editor = {Luis M. Laita, L. de Ledesma, E. Roanes-Lozano},\n\n  series = {Memorias de la Real Academia de Ciencias, XXXIII},\n\n  address = {Madrid},\n\n  pages = {95--118},\n\n  cicyt = {capitulos},\n\n  note = {},\n\n  annote = {ISBN: 84-87125-44-1}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Planning and scheduling for workflow domains.\n \n \n \n \n\n\n \n Rodríguez-Moreno, M. D.; Borrajo, D.; Oddi, A.; Cesta, A.; and Meziat, D.\n\n\n \n\n\n\n of Frontiers in Artificial Intelligence and Applications. Planning, Scheduling and Constraint Satisfaction: from Theory to Practice, pages 169-178. Luis Castillo, D. B.; and Oddi, A., editor(s). IOS Press, 2005.\n \n\n\n\n
\n\n\n\n \n \n $\"Planning,$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inbook{ecai04-workshop,\n\n  author = {María Dolores Rodríguez-Moreno and Daniel\n\n                  Borrajo and Angelo Oddi and Amedeo Cesta and Daniel Meziat},\n\n  title = {Planning, Scheduling and Constraint Satisfaction: from Theory to Practice},\n\n  chapter = {Planning and scheduling for workflow domains},\n\n  editor = {Luis Castillo, Daniel Borrajo, Miguel A. Salido and Angelo Oddi},\n\n  year = {2005},\n\n  cicyt = {capitulos},\n\n  url = {ecai04-workshop.pdf},\n\n  key = {Organisations modelling},\n\n  publisher = {IOS Press},\n\n  series = {Frontiers in Artificial Intelligence and Applications},\n\n  pages = {169-178}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Reinforcement Learning Algorithm in Cooperative Multi-Robot Domains.\n \n \n \n \n\n\n \n Fernández, F.; Borrajo, D.; and Parker, L.\n\n\n \n\n\n\n Journal of Intelligent and Robotic Systems, 43(2–4): 161–174. August 2005.\n http://dx.doi.org/10.1007/s10846-005-5137-x\n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jirs05,\n\n  author = {Fernando Fernández and Daniel Borrajo and Lynne Parker},\n\n  title = {A Reinforcement Learning Algorithm in Cooperative Multi-Robot Domains},\n\n  journal = {Journal of Intelligent and Robotic Systems},\n\n  year = {2005},\n\n  publisher = {Springer Verlag},\n\n  url = {http://hdl.handle.net/10016/6795},\n\n  volume = {43},\n\n  number = {2--4},\n\n  key = {Reactive},\n\n  month = {August},\n\n  cicyt = {revista},\n\n  jcr = {Q4, 2005: 0.219 (72/79)},\n\n  optjcr = {2004: 0.254 (69/78), 2005: 0.219 (72/79), 2006: 0.265 (79/85), 2007: 0.459 (75/93)},\n\n  pages = {161--174},\n\n  annote = {.// En Categoría Robotics: 2007 (10/13)},\n\n  note = {http://dx.doi.org/10.1007/s10846-005-5137-x}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Predicting Opponent Actions by Observation.\n \n \n \n \n\n\n \n Ledezma, A.; Aler, R.; Sanchis, A.; and Borrajo, D.\n\n\n \n\n\n\n In Nardi, D.; Riedmiller, M.; and Sammut, C., editor(s), RoboCup 2004: Robot Soccer World Cup VIII, volume 3276, of Lecture Notes in Computer Science, pages 286-296, Lisbon (Portugal), 2005. Springer Verlag\n http://dx.doi.org/10.1007/978-3-540-32256-6_23\n\n\n\n
\n\n\n\n \n \n $\"Predicting$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{robosoccer05,\n\n  author = {Agapito Ledezma and Ricardo Aler and Araceli Sanchis and Daniel Borrajo},\n\n  booktitle = {{RoboCup 2004: Robot Soccer World Cup VIII}},\n\n  title = {Predicting Opponent Actions by Observation},\n\n  publisher = {Springer Verlag},\n\n  year = {2005},\n\n  key = {Multi-Agent Learning},\n\n  url = {http://hdl.handle.net/10016/5868},\n\n  editor = {Daniele Nardi and Martin Riedmiller and Claude Sammut},\n\n  volume = {3276},\n\n  optnumber = {},\n\n  series = {Lecture Notes in Computer Science},\n\n  cicyt = {lncs},\n\n  address = {Lisbon (Portugal)},\n\n  optedition = {},\n\n  optmonth = {},\n\n  pages = {286-296},\n\n  opttype = {},\n\n  note = {http://dx.doi.org/10.1007/978-3-540-32256-6_23},\n\n  annote = {ISSN: 0302-9743, ISBN: 3-540-25046-8},\n\n  jcr = {B}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Machine Learning in Hybrid Hierarchical and Partial-Order Planners for Manufacturing Domains.\n \n \n \n \n\n\n \n Fernández, S.; Aler, R.; and Borrajo, D.\n\n\n \n\n\n\n Applied Artificial Intelligence, 19(8): 783–809. September 2005.\n http://dx.doi.org/10.1080/08839510490964491\n\n\n\n
\n\n\n\n \n \n $\"Machine$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{applied05,\n\n  author = {Susana Fernández and Ricardo Aler and Daniel Borrajo},\n\n  title = {Machine Learning in Hybrid Hierarchical and Partial-Order Planners for Manufacturing Domains},\n\n  journal = {Applied Artificial Intelligence},\n\n  year = {2005},\n\n  url = {http://hdl.handle.net/10016/5826},\n\n  key = {Planning-Learning},\n\n  volume = {19},\n\n  number = {8},\n\n  month = {September},\n\n  pages = {783--809},\n\n  cicyt = {revista},\n\n  jcr = {Q3, 2005: 0.629 (56/79), En Categoría Engineering, Electrical \\& Electronic: 2005: 116/208},\n\n  optjcr = {2004: 0.556 (54/78), 2005: 0.629 (56/79), 2006: 0.576 (63/85), 2007: 0.753 (58/93)\\\\ En Categoría Engineering, Electrical \\& Electronic: 2005: 116/208},\n\n  publisher = {Taylor \\& Francis},\n\n  annote = {ISSN:0883-9514 print/1087-6545 online. DOI: 10.1080/08839510490964491},\n\n  note = {http://dx.doi.org/10.1080/08839510490964491}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Multi-Agent Architecture for Intelligent Gathering Systems.\n \n \n \n \n\n\n \n Camacho, D.; Aler, R.; Borrajo, D.; and Molina, J. M.\n\n\n \n\n\n\n AI Communications, 18(1): 15–32. 2005.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aicomm05,\n\n  author = {David Camacho and Ricardo Aler and Daniel Borrajo and José\n\n                  Manuel Molina},\n\n  title = {A Multi-Agent Architecture for Intelligent Gathering Systems},\n\n  journal = {AI Communications},\n\n  year = {2005},\n\n  url = {http://hdl.handle.net/10016/5898},\n\n  publisher = {IOS Press},\n\n  key = {Planning-Web},\n\n  volume = {18},\n\n  number = {1},\n\n  cicyt = {revista},\n\n  jcr = {Q3, 2005: 0.612 (57/79)},\n\n  optjcr = {2004: 0.738 (42/78), 2005: 0.612 (57/79), 2006: 0.469 (69/85), 2007: 0.585 (68/93)},\n\n  pages = {15--32}\n\n}\n\n\n\n

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\n \n 2004\n \n \n (14)\n \n \n

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\n \n\n \n \n \n \n \n \n A Unified Approach to Scheduling and Resource Analysis for the Galileo Mission.\n \n \n \n \n\n\n \n Linares López, C.; Castro, A.; and López, I.\n\n\n \n\n\n\n In Proceedings of the Fourth International Workshop on Planning and Scheduling for Space (IWPSS'04), volume WPP-228, pages 320–328, Darmstadt, Germany, June 2004. European Space Agency\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c.castro.a.ea:unified,\n  author\t= {Carlos {Linares L\\'opez} and Antonio Castro and Ismael\n\t\t  L\\'opez},\n  title\t\t= {A Unified Approach to Scheduling and Resource Analysis for\n\t\t  the {G}alileo Mission},\n  booktitle\t= {Proceedings of the Fourth International Workshop on\n\t\t  Planning and Scheduling for Space (IWPSS'04)},\n  pages\t\t= {320--328},\n  year\t\t= {2004},\n  month\t\t= jun,\n  volume\t= {WPP-228},\n  address\t= {Darmstadt, Germany},\n  publisher\t= {European Space Agency},\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/iwpss.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n On the Heuristic Performance of Perimeter Search Algorithms.\n \n \n \n \n\n\n \n Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Tenth Conference of the Spanish Association for Artificial Intelligence (CAEPIA'03), volume 3040, of Lecture Notes in Artificial Intelligence, pages 445–456, San Sebastián, Spain, November 2004. Springer-Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"On$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c:on,\n  author\t= {Carlos {Linares L\\'opez}},\n  title\t\t= {On the Heuristic Performance of Perimeter Search\n\t\t  Algorithms},\n  booktitle\t= {Proceedings of the Tenth Conference of the Spanish\n\t\t  Association for Artificial Intelligence (CAEPIA'03)},\n  pages\t\t= {445--456},\n  year\t\t= {2004},\n  volume\t= {3040},\n  series\t= {Lecture Notes in Artificial Intelligence},\n  address\t= {San Sebastián, Spain},\n  month\t\t= nov,\n  publisher\t= {Springer-Verlag},\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/caepia03.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n A Study on the Accuracy of Heuristic Functions.\n \n \n \n \n\n\n \n Linares López, C.\n\n\n \n\n\n\n In Proceedings of the Sixteenth European Conference on Artificial Intelligence (ECAI'04), pages 201–205, Valencia, Spain, August 2004. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c:study,\n  author\t= {Carlos {Linares L\\'opez}},\n  title\t\t= {A Study on the Accuracy of Heuristic Functions},\n  booktitle\t= {Proceedings of the Sixteenth European Conference on\n\t\t  Artificial Intelligence (ECAI'04)},\n  pages\t\t= {201--205},\n  month\t\t= aug,\n  year\t\t= {2004},\n  address\t= {Valencia, Spain},\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/ecai2004.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Learning Content Sequencing in an Educational Environment According to Student Needs.\n \n \n \n \n\n\n \n Iglesias, A.; Mart?nez, P.; Aler, R.; and Fern?ndez, F.\n\n\n \n\n\n\n In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), volume 3244, pages 454–463. 2004.\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{Iglesias2004,\nabstract = {One of the most important issues in educational systems is to define effective teaching policies according to the students learning characteristics. This paper proposes to use the Reinforcement Learning (RL) model in order for the system to learn automatically sequence of contents to be shown to the student, based only in interactions with other students, like human tutors do. An initial clustering of the students according to their learning characteristics is proposed in order the system adapts better to each student. Experiments show convergence to optimal teaching tactics for different clusters of simulated students, concluding that the convergence is faster when the system tactics have been previously initialised. {\\textcopyright} Springer-Verlag Berlin Heidelberg 2004.},\nauthor = {Iglesias, Ana and Mart?nez, Paloma and Aler, Ricardo and Fern?ndez, Fernando},\nbooktitle = {Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)},\ndoi = {10.1007/978-3-540-30215-5_34},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F978-3-540-30215-5{\\_}34.pdf:pdf},\nissn = {03029743},\npages = {454--463},\ntitle = {{Learning Content Sequencing in an Educational Environment According to Student Needs}},\nurl = {https://link.springer.com/chapter/10.1007{\\%}2F978-3-540-30215-5{\\_}34 http://link.springer.com/10.1007/978-3-540-30215-5{\\_}34},\nvolume = {3244},\nyear = {2004}\n}\n

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\n \n\n \n \n \n \n \n \n Evolutionary Design of Nearest Prototype Classifiers.\n \n \n \n \n\n\n \n Fernández, F.; and Isasi, P.\n\n\n \n\n\n\n Journal of Heuristics, 10(4): 431–454. jul 2004.\n \n\n\n\n
\n\n\n\n \n \n $\"Evolutionary$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Fernandez2004,\nabstract = {In pattern classification problems, many works have been carried out with the aim of designing good classifiers from different perspectives. These works achieve very good results in many domains. However, in general they are very dependent on some crucial parameters involved in the design, These parameters have to be found by a trial and error process or by some automatic methods, like heuristic search and genetic algorithms, that strongly decrease the performance of the method. For instance, in nearest prototype approaches, main parameters are the number of prototypes to use, the initial set, and a smoothing parameter. In this work, an evolutionary approach based on Nearest Prototype Classifier (ENPC) is introduced where no parameters are involved, thus overcoming all the problems that classical methods have in tuning and searching for the appreciate values. The algorithm is based on the evolution of a set of prototypes that can execute several operators in order to increase their quality in a local sense, and with a high classification accuracy emerging for the whole classifier. This new approach has been tested using four different classical domains, including such artificial distributions as spiral and uniform distibuted data sets, the Iris Data Set and an application domain about diabetes. In all the cases, the experiments show successfull results, not only in the classification accuracy, but also in the number and distribution of the prototypes achieved.},\nauthor = {Fern{\\'{a}}ndez, Fernando and Isasi, Pedro},\ndoi = {10.1023/B:HEUR.0000034715.70386.5b},\nfile = {:home/fernando/papers/tmp/10.1023{\\%}2FB-HEUR.0000034715.70386.5b.pdf:pdf},\nissn = {1381-1231},\njournal = {Journal of Heuristics},\nkeywords = {Classifier design,Evolutionary learning,Nearest prototype classifiers},\nmonth = {jul},\nnumber = {4},\npages = {431--454},\ntitle = {{Evolutionary Design of Nearest Prototype Classifiers}},\nurl = {http://link.springer.com/10.1023/B:HEUR.0000034715.70386.5b},\nvolume = {10},\nyear = {2004}\n}\n

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\n \n\n \n \n \n \n \n \n Empirical Evaluation of Optimized Stacking Configurations.\n \n \n \n \n\n\n \n Ledezma, A.; Aler, R.; Sanchis, A.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the IEEE International Conference on Tools with Artificial Intelligence, Boca Raton, FL (USA), 2004. IEEE Computer Society\n \n\n\n\n
\n\n\n\n \n \n $\"Empirical$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ictai04,\n\n  author = {Agapito Ledezma and Ricardo Aler and Araceli Sanchis and Daniel Borrajo},\n\n  title = {Empirical Evaluation of Optimized Stacking Configurations},\n\n  booktitle = {Proceedings of the IEEE International Conference\n\n                  on Tools with Artificial Intelligence},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  year = {2004},\n\n  cicyt = {congresos},\n\n  url = {ictai04-stacking.pdf},\n\n  publisher = {IEEE Computer Society},\n\n  address = {Boca Raton, FL (USA)},\n\n  key = {Multi-Agent Learning},\n\n  month = {},\n\n  pages = {},\n\n  jcr = {B}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using Previous Experience for Learning Planning Control Knowledge.\n \n \n \n \n\n\n \n Fernández, S.; Aler, R.; and Borrajo, D.\n\n\n \n\n\n\n In Barr, V.; and Markov, Z., editor(s), Proceedings of the Seventeen International Florida Artificial Intelligence (FLAIRS04), pages 713-718, Miami Beach, FL (USA), May 2004. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{flairs04,\n\n  author = {Susana Fernández and Ricardo Aler and Daniel Borrajo},\n\n  title = {Using Previous Experience for Learning Planning Control Knowledge},\n\n  booktitle = {Proceedings of the Seventeen International Florida Artificial Intelligence (FLAIRS04)},\n\n  pages = {713-718},\n\n  year = {2004},\n\n  editor = {Valerie Barr and Zdravko Markov},\n\n  address = {Miami Beach, FL (USA)},\n\n  month = {May},\n\n  cicyt = {congresos},\n\n  publisher = {AAAI Press},\n\n  key = {Planning-Learning},\n\n  url = {flairs04.pdf},\n\n  jcr = {C}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n An AI Planning-based Tool for Scheduling Satellite Nominal Operations.\n \n \n \n \n\n\n \n Rodríguez-Moreno, M. D.; Borrajo, D.; and Meziat, D.\n\n\n \n\n\n\n AI Magazine, 25(4): 9–27. Winter 2004.\n http://www.aaai.org/ojs/index.php/aimagazine/article/viewArticle/1782\n\n\n\n
\n\n\n\n \n \n $\"An$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ai-magazine,\n\n  author = {María Dolores Rodríguez-Moreno and Daniel Borrajo and Daniel Meziat},\n\n  title = {An {AI} Planning-based Tool for Scheduling Satellite Nominal Operations},\n\n  journal = {AI Magazine},\n\n  year = {2004},\n\n  key = {Planning-Learning},\n\n  url = {http://hdl.handle.net/10016/6792},\n\n  volume = {25},\n\n  number = {4},\n\n  month = {Winter},\n\n  publisher = {AAAI Press},\n\n  cicyt = {revista},\n\n  jcr = {Q2, 2004: 1.291 (25/78)},\n\n  optjcr = {2004: 1.291 (25/78), 2005: 1.521 (28/79), 2006: 1.000 (38/85), 2007: 1.304 (36/93)},\n\n  pages = {9--27},\n\n  annote = {ISSN: 0738-4602},\n\n  note = {http://www.aaai.org/ojs/index.php/aimagazine/article/viewArticle/1782}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n A Unified Approach to Scheduling and Resource Analysis for the Galileo Mission.\n \n \n \n\n\n \n Linares, C.; Castro, A.; and López, I.\n\n\n \n\n\n\n In $4^{\\mbox{th}}$ International Workshop on Planning and Scheduling for Space (IWPSS'04), volume WPP-228, pages 320–328, Darmstadt, Germany, June 2004. European Space Agency\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{linares.c.castro.a.ea:unified,\n\n  author = {Carlos Linares and Antonio Castro and Ismael L\\'opez},\n\n  title = {A Unified Approach to Scheduling and Resource Analysis for the Galileo Mission},\n\n  booktitle = {$4^{\\mbox{th}}$ International Workshop on Planning and Scheduling for Space (IWPSS'04)},\n\n  cicyt = {workshops},\n\n  pages = {320--328},\n\n  year = {2004},\n\n  month = jun,\n\n  volume = {WPP-228},\n\n  key = {Planning-Learning},\n\n  address = {Darmstadt, Germany},\n\n  publisher = {European Space Agency}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n A Study on the Accuracy of Heuristic Functions.\n \n \n \n\n\n \n Linares, C.\n\n\n \n\n\n\n In de Mántaras, R. L.; and Saitta, L., editor(s), $16^{\\mbox{th}}$ European Conference on Artificial Intelligence (ECAI'04), pages 201–205, Valencia, Spain, August 2004. IOS Press\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{linares.c:study,\n\n  author = {Carlos Linares},\n\n  title = {A Study on the Accuracy of Heuristic Functions},\n\n  booktitle = {$16^{\\mbox{th}}$ European Conference on Artificial Intelligence (ECAI'04)},\n\n  key = {Search},\n\n  pages = {201--205},\n\n  month = aug,\n\n  year = {2004},\n\n  editor = {Ram\\'on L\\'opez de M\\'antaras and Lorenza Saitta},\n\n  cicyt = {congresos-buenos},\n\n  address = {Valencia, Spain},\n\n  publisher = {{IOS} Press}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n On the Heuristic Performance of Perimeter Search Algorithms.\n \n \n \n\n\n \n Linares, C.\n\n\n \n\n\n\n Lecture Notes in Artificial Intelligence, 3040: 445–456. November 2004.\n Proceedings of the X Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA'03)\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{linares.c:on,\n\n  author = {Carlos Linares},\n\n  title = {On the Heuristic Performance of Perimeter Search\n\n         Algorithms},\n\n  journal = {Lecture Notes in Artificial Intelligence},\n\n  year = {2004},\n\n  volume = {3040},\n\n  pages = {445--456},\n\n  cicyt = {lncs},\n\n  key = {Search},\n\n  note = {Proceedings of the X Conferencia de la Asociaci\\'on Espa\\~nola\n\n         para la Inteligencia Artificial (CAEPIA'03)},\n\n  editor = {Ricardo Conejo and Maite Urretavizcaya and José Luis Pérez de la Cruz},\n\n  address = {San Sebasti\\'an (Spain)},\n\n  month = nov,\n\n  publisher = {Springer-Verlag}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Evolutionary Design of Nearest Prototype Classifiers.\n \n \n \n\n\n \n Fernández, F.; and Isasi, P.\n\n\n \n\n\n\n Journal of Heuristics, 10(4): 431-454. 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{fernandez04a,\n\n  author = {Fernando Fern\\'andez and Pedro Isasi},\n\n  title = {Evolutionary Design of Nearest Prototype Classifiers},\n\n  journal = {Journal of Heuristics},\n\n  year = {2004},\n\n  volume = {10},\n\n  number = {4},\n\n  key = {Reactive},\n\n  pages = {431-454},\n\n  cicyt = {revista},\n\n  publisher = {Kluwer}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Learning Content Sequencing in an Educational Environment According Student Need.\n \n \n \n\n\n \n Iglesias, A. M.; Martínez, P.; Aler, R.; and Fernández, F.\n\n\n \n\n\n\n , (3244): 454 - 463. 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{iglesias04,\n\n  author = {Ana Mª Iglesias and Paloma Martínez and Ricardo Aler and Fernando Fernández},\n\n  title = {Learning Content Sequencing in an Educational Environment According Student Need},\n\n  booktitle = {Algorithmic Learning Theory: 15th International Conference, ALT 2004},\n\n  pages = {454 - 463},\n\n  publisher = {Springer-Verlag},\n\n  key = {Reactive},\n\n  year = {2004},\n\n  number = {3244},\n\n  cicyt = {lncs},\n\n  series = {Lecture Notes on Computer Sciences}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Management of Patients with Diabetes Through Information Technology: Tools for Monitoring and Control of the Patients' Metabolic Behavior.\n \n \n \n\n\n \n Bellazzi, R.; Arcelloni, M.; Ferrari, P.; Decata, P.; Hernando, M.; Garcia, A.; Gazzaruso, C.; Gomez, E.; Larizza, C.; Fratino, P.; and Stefanelli, M.\n\n\n \n\n\n\n Diabetes Technology and Therapeutics, 6(5): 567- 578. 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Bellazzi04,\n\n  author = {R. Bellazzi and M. Arcelloni and P. Ferrari and P. Decata and M. Hernando and A. Garcia and C. Gazzaruso and E. Gomez and C. Larizza and P. Fratino and M. Stefanelli},\n\n  title = {Management of Patients with Diabetes Through Information Technology: Tools for Monitoring and Control of the Patients' Metabolic Behavior},\n\n  year = {2004},\n\n  journal = {Diabetes Technology and Therapeutics},\n\n  pages = {567- 578},\n\n  volume = {6},\n\n  number = {5},\n\n  key = {Other},\n\n  cicyt = {revista-noJCR}\n\n}\n\n\n\n

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\n \n 2003\n \n \n (12)\n \n \n

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\n \n\n \n \n \n \n \n \n Perimeter Search Performance.\n \n \n \n \n\n\n \n Linares López, C.; and Junghanns, A.\n\n\n \n\n\n\n In Proceedings of Computers and Games 2002 (CG'02), volume 2883, of Lecture Notes in Computer Science, pages 345–359, Edmonton, Canada, July 2003. Springer-Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Perimeter$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c.junghanns.a:perimeter,\n  author\t= {Carlos {Linares L\\'opez} and Andreas Junghanns},\n  title\t\t= {Perimeter Search Performance},\n  booktitle\t= {Proceedings of Computers and Games 2002 (CG'02)},\n  pages\t\t= {345--359},\n  year\t\t= {2003},\n  volume\t= {2883},\n  series\t= {Lecture Notes in Computer Science},\n  address\t= {Edmonton, Canada},\n  month\t\t= jul,\n  publisher\t= {Springer-Verlag},\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/cg2002.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n From continuous behaviour to discrete knowledge.\n \n \n \n\n\n \n Ledezma, A.; Fernández, F.; and Aler, R.\n\n\n \n\n\n\n Volume 2687 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@book{Ledezma2003,\nabstract = {Neural networks have proven to be very powerful techniques for solving a wide range of tasks. However, the learned concepts are unreadable for humans. Some works try to obtain symbolic models from the networks, once these networks have been trained, allowing to understand the model by means of decision trees or rules that are closer to human understanding. The main problem of this approach is that neural networks output a continuous range of values, so even though a symbolic technique could be used to work with continuous classes, this output would still be hard to understand for humans. In this work, we present a system that is able to model a neural network behaviour by discretizing its outputs with a vector quantization approach, allowing to apply the symbolic method. {\\textcopyright} Springer-Verlag Berlin Heidelberg 2003.},\nauthor = {Ledezma, A. and Fern{\\'{a}}ndez, F. and Aler, R.},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\nissn = {03029743},\ntitle = {{From continuous behaviour to discrete knowledge}},\nvolume = {2687},\nyear = {2003}\n}\n

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\n \n\n \n \n \n \n \n \n From Continuous Behaviour to Discrete Knowledge.\n \n \n \n \n\n\n \n Ledezma, A.; Fernández, F.; and Aler, R.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 2687, pages 217–224. 2003.\n \n\n\n\n
\n\n\n\n \n \n $\"From$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{Ledezma2003a,\nabstract = {Neural networks have proven to be very powerful techniques for solving a wide range of tasks. However, the learned concepts are unreadable for humans. Some works try to obtain symbolic models from the networks, once these networks have been trained, allowing to understand the model by means of decision trees or rules that are closer to human understanding. The main problem of this approach is that neural networks output a continuous range of values, so even though a symbolic technique could be used to work with continuous classes, this output would still be hard to understand for humans. In this work, we present a system that is able to model a neural network behaviour by discretizing its outputs with a vector quantization approach, allowing to apply the symbolic method. {\\textcopyright} Springer-Verlag Berlin Heidelberg 2003.},\nauthor = {Ledezma, Agapito and Fern{\\'{a}}ndez, Fernando and Aler, Ricardo},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\ndoi = {10.1007/3-540-44869-1_28},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F3-540-44869-1{\\_}28.pdf:pdf},\nissn = {03029743},\npages = {217--224},\ntitle = {{From Continuous Behaviour to Discrete Knowledge}},\nurl = {http://link.springer.com/10.1007/3-540-44869-1{\\_}28},\nvolume = {2687},\nyear = {2003}\n}\n

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\n \n\n \n \n \n \n \n \n Navigating through the RLATES Interface: A Web-Based Adaptive and Intelligent Educational System.\n \n \n \n \n\n\n \n Iglesias, A.; Martínez, P.; and Fernández, F.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 2889, pages 175–184. 2003.\n \n\n\n\n
\n\n\n\n \n \n $\"Navigating$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{Iglesias2003,\nabstract = {The paper shows the architecture of the RLATES system, an Adaptive and Intelligent Educational System that uses the Reinforcement Learning model (RL) in order to learn to teach each student individually, being adapted to their learning needs in each moment of the interaction. This papers is focused on the interface module of RLATES, describing how the student could navigate through the system interface and how this interface adjusts the page contents according to the user learning needs. For this adaptation, the system changes the links appearance of the page and the presentation of the system knowledge. {\\textcopyright} Springer-Verlag Berlin Heidelberg 2003.},\nauthor = {Iglesias, Ana and Mart{\\'{i}}nez, Paloma and Fern{\\'{a}}ndez, Fernando},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\ndoi = {10.1007/978-3-540-39962-9_29},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F978-3-540-39962-9{\\_}29.pdf:pdf},\nissn = {03029743},\npages = {175--184},\ntitle = {{Navigating through the RLATES Interface: A Web-Based Adaptive and Intelligent Educational System}},\nurl = {http://link.springer.com/10.1007/978-3-540-39962-9{\\_}29},\nvolume = {2889},\nyear = {2003}\n}\n

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\n \n\n \n \n \n \n \n \n Evolutionary Approach to Overcome Initialization Parameters in Classification Problems.\n \n \n \n \n\n\n \n Isasi, P.; and Fernandez, F.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 2686, pages 254–261. 2003.\n \n\n\n\n
\n\n\n\n \n \n $\"Evolutionary$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{Isasi2003,\nabstract = {The design of nearest neighbour classifiers is very dependent from some crucial parameters involved in learning, like the number of prototypes to use, the initial localization of these prototypes, and a smoothing parameter. These parameters have to be found by a trial and error process or by some automatic methods. In this work, an evolutionary approach based on Nearest Neighbour Classifier (ENNC), is described. Main property of this algorithm is that it does not require any of the above mentioned parameters. The algorithm is based on the evolution of a set of prototypes that can execute several operators in order to increase their quality in a local sense, and emerging a high classification accuracy for the whole classifier. {\\textcopyright} Springer-Verlag Berlin Heidelberg 2003.},\nauthor = {Isasi, P. and Fernandez, F.},\nbooktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},\ndoi = {10.1007/3-540-44868-3_33},\nfile = {:home/fernando/papers/tmp/10.1007{\\%}2F3-540-44868-3{\\_}33.pdf:pdf},\nissn = {03029743},\npages = {254--261},\ntitle = {{Evolutionary Approach to Overcome Initialization Parameters in Classification Problems}},\nurl = {http://link.springer.com/10.1007/3-540-44868-3{\\_}33},\nvolume = {2686},\nyear = {2003}\n}\n

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\n \n\n \n \n \n \n \n \n Technological Roadmap on AI Planning and Scheduling.\n \n \n \n \n\n\n \n Biundo, S.; Aylett, R.; Beetz, M.; Borrajo, D.; Cesta, A.; Grant, T.; McCluskey, L.; Milani, A.; and Verfaille, G.\n\n\n \n\n\n\n PLANET, 2003.\n \n\n\n\n
\n\n\n\n \n \n $\"Technological$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@book{planet-II-roadmap,\n\n  author = {Susanne Biundo and Ruth Aylett and Michael Beetz and Daniel\n\n                  Borrajo and Amedeo Cesta and Tim Grant and Lee McCluskey and\n\n                  Alfredo Milani and Gérard Verfaille},\n\n  title = {Technological Roadmap on {AI} Planning and Scheduling},\n\n  publisher = {PLANET},\n\n  cicyt = {otras-publicaciones},\n\n  year = {2003},\n\n  key = {Planning-Learning},\n\n  annote = {http://www.planet-noe.org/},\n\n  url = {planet-roadmap.pdf}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n PLANET Workflow Management R&D Roadmap.\n \n \n \n \n\n\n \n Kearney, P.; Borrajo, D.; Cesta, A.; Matino, N.; and Mehandjiev, N.\n\n\n \n\n\n\n PLANET, 2003.\n \n\n\n\n
\n\n\n\n \n \n $\"PLANET$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@book{roadmap-wm,\n\n  author = {Paul Kearney and Daniel Borrajo and Amedeo Cesta and Nicola\n\n                  Matino and Nikolay Mehandjiev},\n\n  title = {PLANET Workflow Management {R}\\&{D} Roadmap},\n\n  cicyt = {otras-publicaciones},\n\n  publisher = {PLANET},\n\n  key = {Organisations modelling},\n\n  year = {2003},\n\n  url = {http://www.plg.inf.uc3m.es/~dborrajo/planet/wm-tcu/}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Learning Retrieval Expert Combinations with Genetic Algorithms.\n \n \n \n \n\n\n \n Billhardt, H.; Borrajo, D.; and Maojo, V.\n\n\n \n\n\n\n International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(1): 87–114. February 2003.\n http://dx.doi.org/10.1142/S0218488503001965\n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ijufks,\n\n  author = {Holger Billhardt and Daniel Borrajo and Victor Maojo},\n\n  title = {Learning Retrieval Expert Combinations with Genetic\n\n                  Algorithms},\n\n  journal = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},\n\n  year = {2003},\n\n  publisher = {World Scientific},\n\n  month = {February},\n\n  url = {http://hdl.handle.net/10016/6744},\n\n  key = {Learning-Information Retrieval},\n\n  volume = {11},\n\n  number = {1},\n\n  cicyt = {revista},\n\n  jcr = {Q4, 2003: 0.487 (61/77)},\n\n  optjcr = {2003: 0.487 (61/77), 2004: 0.573 (52/78), 2005: 0.430 (67/79), 2006: 0.406 (72/85), 2007: 0.376 (81/93)},\n\n  pages = {87--114},\n\n  annote = {ISSN: 0218-4885},\n\n  note = {http://dx.doi.org/10.1142/S0218488503001965}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Perimeter Search Performance.\n \n \n \n\n\n \n Linares, C.; and Junghanns, A.\n\n\n \n\n\n\n Lecture Notes in Computer Science, 2883: 345–359. July 2003.\n Proceedings of Computers and Games 2002 (CG'02)\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{linares.c.junghanns.a:perimeter,\n\n  author = {Carlos Linares and Andreas Junghanns},\n\n  title = {Perimeter Search Performance},\n\n  journal = {Lecture Notes in Computer Science},\n\n  year = {2003},\n\n  month = jul,\n\n  volume = {2883},\n\n  pages = {345--359},\n\n  cicyt = {lncs},\n\n  key = {Search},\n\n  note = {Proceedings of Computers and Games 2002 (CG'02)},\n\n  address = {Edmonton (Canada)},\n\n  editor = {Jonathan Schaeffer and Martin M\\"uller and Yngvi\n\n         Bj\\"ornsson},\n\n  publisher = {Springer-Verlag}\n\n}\n\n\n\n

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\n\n\n\n

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\n \n\n \n \n \n \n \n Design, Methods, and Evaluation Directions of a Multi-Access Service for the Management of Diabetes Mellitus Patients.\n \n \n \n\n\n \n Bellazzi, R.; Arcelloni, M.; Bensa, G.; Blankenfeld, H.; Brugués, E.; Carson, E.; Cobelli, C.; D.Cramp; G.d'annunzio; Cata, P.; Leiva, A.; T.Deutsch; Fratino, P.; Gazzaruso, C.; García, A.; Gergely, T.; Gómez, E.; Harvey, F.; Ferrari, P.; Hernando, E.; andC.Larizza , M.; Ludekke, H.; Maran, A.; Nucci, G.; Pennati, C.; Ramat, S.; Roudsari, A.; Rigla, M.; and Stefanelli, M.\n\n\n \n\n\n\n Diabetes Technology and Therapeutics, 5(4): 621-629. 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Bellazzi03,\n\n  author = {R. Bellazzi and M. Arcelloni and G. Bensa and H. Blankenfeld and E. Brugués and E. Carson and C. Cobelli and D.Cramp and G.d'annunzio and P.de Cata and A.de Leiva and T.Deutsch and P. Fratino and C. Gazzaruso and A. García and T. Gergely and E. Gómez and F. Harvey and P. Ferrari and E. Hernando and M.K.Boulos andC.Larizza and H. Ludekke and A. Maran and G. Nucci and C. Pennati and S. Ramat and A. Roudsari and M. Rigla and M. Stefanelli},\n\n  title = {Design, Methods, and Evaluation Directions of a Multi-Access Service for the Management of Diabetes Mellitus Patients},\n\n  year = {2003},\n\n  journal = {Diabetes Technology and Therapeutics},\n\n  pages = {621-629},\n\n  volume = {5},\n\n  number = {4},\n\n  key = {Other},\n\n  cicyt = {revista-noJCR}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Middleware Technologies for Telemedicine-Based Diabetes Shared Care.\n \n \n \n\n\n \n García-Olaya, A.; Gómez, E. J.; Hernando, M. E.; Perdices, F. J.; and del Pozo, F.\n\n\n \n\n\n\n Diabetes Technology and Therapeutics, 5(2): 241. 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Garcia03,\n\n  author = {Angel García-Olaya and Enrique J. Gómez and M. Elena Hernando and F. Javier Perdices and Francisco del Pozo},\n\n  title = {Middleware Technologies for Telemedicine-Based Diabetes Shared Care},\n\n  year = {2003},\n\n  journal = {Diabetes Technology and Therapeutics},\n\n  pages = {241},\n\n  volume = {5},\n\n  number = {2},\n\n  key = {Other},\n\n  cicyt = {revista-noJCR}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n The use of a multi-access service for the diabetes management allows better glycaemic control in insulin treated diabetic patients.\n \n \n \n\n\n \n Rigla-Cros, M.; Brugués, E.; Gomez, E.; Hernando, M.; Garcia-Olaya, A.; Perdices, F.; V.Torralba; and Leiva, A. D.\n\n\n \n\n\n\n Diabetologia, 46(S2): A426. 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Rigla02,\n\n  author = {M. Rigla-Cros and E. Brugués and E.J. Gomez and M.E. Hernando and A. Garcia-Olaya and F.J. Perdices and V.Torralba and A. De Leiva},\n\n  title = {The use of a multi-access service for the diabetes management allows better glycaemic control in insulin treated diabetic patients},\n\n  year = {2003},\n\n  journal = {Diabetologia},\n\n  pages = {A426},\n\n  volume = {46},\n\n  number = {S2},\n\n  language = {english},\n\n  key = {Other},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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\n \n 2002\n \n \n (17)\n \n \n

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\n \n\n \n \n \n \n \n Learning to teach database design by trial and error.\n \n \n \n\n\n \n Iglesias, A.; Martínez, P.; Cuadra, D.; Castro, E.; and Fernández, F.\n\n\n \n\n\n\n In ICEIS 2002 - Proceedings of the 4th International Conference on Enterprise Information Systems, volume 1, 2002. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@inproceedings{Iglesias2002,\nabstract = {The definition of effective pedagogical strategies for coaching and tutoring students according to their needs in each moment is a high handicap in ITS design. In this paper we propose the use of a Reinforcement Learning (RL) model, that allows the system to learn how to teach to each student individually, only based on the acquired experience with other learners with similar characteristics, like a human tutor does. This technique avoids to define the teaching strategies by learning action policies that define what, when and how to teach. The model is applied to a database design ITS system, used as an example to illustrate all the concepts managed in the model.},\nauthor = {Iglesias, A. and Mart{\\'{i}}nez, P. and Cuadra, D. and Castro, E. and Fern{\\'{a}}ndez, F.},\nbooktitle = {ICEIS 2002 - Proceedings of the 4th International Conference on Enterprise Information Systems},\nisbn = {9729805067},\nkeywords = {Coaching and tutoring,Intelligent tutoring system,Pedagogical strategies,Reinforcement Learning},\ntitle = {{Learning to teach database design by trial and error}},\nvolume = {1},\nyear = {2002}\n}\n

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\n \n\n \n \n \n \n \n \n Automatic finding of good classifiers following a biologically inspired metaphor.\n \n \n \n \n\n\n \n Fernández, F.; and Isasi, P.\n\n\n \n\n\n\n Computing and Informatics, 21(3). 2002.\n \n\n\n\n
\n\n\n\n \n \n $\"Automatic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Fernandez2002,\nabstract = {The design of nearest neighbour classifiers can be seen as the partitioning of the whole domain in different regions that can be directly mapped to a class. The definition of the limits of these regions is the goal of any nearest neighbour based algorithm. These limits can be described by the location and class of a reduced set of prototypes and the nearest neighbour rule. The nearest neighbour rule can be defined by any distance metric, while the set of prototypes is the matter of design. To compute this set of prototypes, most of the algorithms in the literature require some crucial parameters as the number of prototypes to use, and a smoothing parameter. In this work, an evolutionary approach based on Nearest Neighbour Classifiers (ENNC) is introduced where no parameters are involved, thus overcoming all the problems derived from the use of the above mentioned parameters. The algorithm follows a biological metaphor where each prototype is identified with an animal, and the regions of the prototypes with the territory of the animals. These animals evolve in a competitive environment with a limited set of resources, emerging a population of animals able to survive in the environment, i.e. emerging a right set of prototypes for the above classification objectives. The approach has been tested using different domains, showing successful results, both in the classification accuracy and the distribution and number of the prototypes achieved.},\nauthor = {Fern{\\'{a}}ndez, F. and Isasi, P.},\nissn = {13359150},\njournal = {Computing and Informatics},\nkeywords = {Biologically inspired algorithms,Classifier design,Evolutionary learning,Nearest neighbour classifiers},\nnumber = {3},\ntitle = {{Automatic finding of good classifiers following a biologically inspired metaphor}},\nurl = {http://www.cai.sk/ojs/index.php/cai/article/viewArticle/497},\nvolume = {21},\nyear = {2002}\n}\n

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\n \n\n \n \n \n \n \n \n Using Genetic Programming to Learn and Improve Control Knowledge.\n \n \n \n \n\n\n \n Aler, R.; Borrajo, D.; and Isasi, P.\n\n\n \n\n\n\n Artificial Intelligence Journal, 141(1-2): 29–56. October 2002.\n http://dx.doi.org/10.1016/S0004-3702(02)00246-1\n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aij-evock,\n\n  author = {Ricardo Aler and Daniel Borrajo and Pedro Isasi},\n\n  title = {Using Genetic Programming to Learn and Improve Control\n\n                  Knowledge},\n\n  journal = {Artificial Intelligence Journal},\n\n  year = {2002},\n\n  url = {http://hdl.handle.net/10016/3937},\n\n  publisher = {Elsevier},\n\n  volume = {141},\n\n  number = {1-2},\n\n  month = {October},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  jcr = {Q1, 2002: 1.769 (10/74)},\n\n  optjcr = {2004: 3.570 (4/78), 2005: 2.368 (7/79), 2006: 2.271 (12/85), 2007: 3.008 (6/93)},\n\n  pages = {29--56},\n\n  annote = {ISSN: 0004-3702},\n\n  note = {http://dx.doi.org/10.1016/S0004-3702(02)00246-1}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Cooperative Distributed Planning Algorithm to Improve Performance in Web Domains.\n \n \n \n \n\n\n \n Camacho, D.; Borrajo, D.; Molina, J. M.; and Aler, R.\n\n\n \n\n\n\n In , editor(s), IEEE International Conference on Systems, Man and Cybernetics, Hammamet, (Tunisia), October 2002. IEEE Press\n http://dx.doi.org/10.1109/ICSMC.2002.1176442\n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{smc02-web,\n\n  author = {David Camacho and Daniel Borrajo and José Manuel Molina and Ricardo Aler},\n\n  title = {A Cooperative Distributed Planning Algorithm to Improve\n\n                  Performance in Web Domains},\n\n  booktitle = {IEEE International Conference on Systems, Man and Cybernetics},\n\n  editor = {},\n\n  year = {2002},\n\n  url = {http://hdl.handle.net/10016/6157},\n\n  key = {Planning-Web},\n\n  cicyt = {congresos},\n\n  publisher = {IEEE Press},\n\n  volumen = {},\n\n  address = {Hammamet, (Tunisia)},\n\n  month = {October},\n\n  pages = {},\n\n  jcr = {B},\n\n  note = {http://dx.doi.org/10.1109/ICSMC.2002.1176442}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Planning and Scheduling – A Technology for Improving Flexibility in ıt e-Commerce and Electronic Work.\n \n \n \n \n\n\n \n Biundo, S.; Borrajo, D.; and McCluskey, L.\n\n\n \n\n\n\n In B. Stanford-Smith, E. C., editor(s), Challenges and Achievements in E-business and E-work, pages 834-841, Prague (Checz Republic), October 2002. IOS Press\n \n\n\n\n
\n\n\n\n \n \n $\"Planning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ebusiness02,\n\n  author = {Susanne Biundo and Daniel Borrajo and Lee McCluskey},\n\n  title = {Planning and Scheduling -- {A} Technology for Improving\n\n                  Flexibility in {\\it e}-Commerce and Electronic Work},\n\n  booktitle = {Challenges and Achievements in E-business and E-work},\n\n  editor = {B. Stanford-Smith, E. Chiozza, M. Edin},\n\n  publisher = {IOS Press},\n\n  cicyt = {congresos},\n\n  year = {2002},\n\n  url = {ebusiness02.rtf},\n\n  key = {Organisations modelling},\n\n  address = {Prague (Checz Republic)},\n\n  month = {October},\n\n  pages = {834-841},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n On Determinism Handling While Learning Reduced State Space Representations.\n \n \n \n \n\n\n \n Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In van Harmelen, F., editor(s), Proceedings of the 15th European Conference on Artificial Intelligence (ECAI 2002), pages 380–384, Lyon (France), July 2002. IOS Press\n \n\n\n\n
\n\n\n\n \n \n $\"On$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ecai02,\n\n  author = {Fernando Fernández and Daniel Borrajo},\n\n  title = {On Determinism Handling While Learning Reduced State Space\n\n                  Representations},\n\n  booktitle = {Proceedings of the 15th European Conference on Artificial\n\n                  Intelligence (ECAI 2002)},\n\n  editor = {F. van Harmelen},\n\n  year = {2002},\n\n  publisher = {IOS Press},\n\n  address = {Lyon (France)},\n\n  month = {July},\n\n  pages = {380--384},\n\n  cicyt = {congresos-buenos},\n\n  url = {ecai02.ps.gz},\n\n  key = {Reactive},\n\n  jcr = {A}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Exploring the Stacking State-space.\n \n \n \n \n\n\n \n Ledezma, A.; Aler, R.; and Borrajo, D.\n\n\n \n\n\n\n International Journal on Artificial Intelligence Tools, 11(2): 267-282. June 2002.\n \n\n\n\n
\n\n\n\n \n \n $\"Exploring$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ijait02,\n\n  author = {Agapito Ledezma and Ricardo Aler and Daniel Borrajo},\n\n  title = {Exploring the Stacking State-space},\n\n  journal = {International Journal on Artificial Intelligence Tools},\n\n  year = {2002},\n\n  volume = {11},\n\n  number = {2},\n\n  month = {June},\n\n  pages = {267-282},\n\n  publisher = {World Scientific Publishing Company},\n\n  url = {http://hdl.handle.net/10016/5790},\n\n  cicyt = {revista},\n\n  jcr = {Entró en 2007: 0.376 (81/93)},\n\n  optjcr = {2007: 0.667 (81/93)},\n\n  key = {Multi-Agent Learning}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Solving Travel Problems by Integrating \\sc web Information with Planning.\n \n \n \n \n\n\n \n Camacho, D.; Molina, J. M.; Borrajo, D.; and Aler, R.\n\n\n \n\n\n\n In Foundations of Intelligent Systems, of Lecture Notes in Artificial Intelligence, pages 482–490, Lyon (France), June 2002. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Solving$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ismis02,\n\n  author = {David Camacho and José Manuel Molina and Daniel Borrajo and Ricardo Aler},\n\n  title = {Solving Travel Problems by Integrating {\\sc web} Information with Planning},\n\n  booktitle = {Foundations of Intelligent Systems},\n\n  pages = {482--490},\n\n  publisher = {Springer Verlag},\n\n  series = {Lecture Notes in Artificial Intelligence},\n\n  cicyt = {lncs},\n\n  number = {LNAI 2366},\n\n  editors = {M-S. Hacid, Z.W. Ras, D.A. Zighed and Y. Kodratoff},\n\n  month = {June},\n\n  address = {Lyon (France)},\n\n  key = {Planning-Web},\n\n  url = {http://hdl.handle.net/10016/5999},\n\n  year = {2002},\n\n  annote = {Proceedings of the XIII International Symposium on Methodologies for\n\n                  Intelligent Systems},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n On Control Knowledge Acquisition by Exploiting Human-Computer Interaction.\n \n \n \n \n\n\n \n Aler, R.; and Borrajo, D.\n\n\n \n\n\n\n In Ghallab, M.; Hertzberg, J.; and Traverso, P., editor(s), Proceedings of the Sixth International Conference on Artificial Intelligence Planning Systems (AIPS-02), pages 112–120, Toulouse (France), April 2002. AAAI Press\n Ponencia\n\n\n\n
\n\n\n\n \n \n $\"On$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{aips02,\n\n  author = {Ricardo Aler and Daniel Borrajo},\n\n  title = {On Control Knowledge Acquisition by Exploiting\n\n                  Human-Computer Interaction},\n\n  booktitle = {Proceedings of the Sixth International Conference on\n\n                  Artificial Intelligence Planning Systems (AIPS-02)},\n\n  editor = {Malik Ghallab and Joachim Hertzberg and Paolo Traverso},\n\n  year = {2002},\n\n  publisher = {AAAI Press},\n\n  address = {Toulouse (France)},\n\n  month = {April},\n\n  pages = {112--120},\n\n  cicyt = {congresos-buenos},\n\n  url = {aips02.ps.gz},\n\n  key = {Planning-Learning},\n\n  note = {Ponencia},\n\n  jcr = {A* (predecesor de ICAPS)}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Learning Single-Criteria Control Knowledge for Multi-Criteria Planning.\n \n \n \n \n\n\n \n Aler, R.; and Borrajo, D.\n\n\n \n\n\n\n In Drabble, B.; Koehler, J.; and Refanidis, I., editor(s), Proceedings of the AIPS-02 Workshop on Planning and Scheduling with Multiple Criteria, pages 35–40, Toulouse (France), April 2002. \n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{aips02-workshop,\n\n  author = {Ricardo Aler and Daniel Borrajo},\n\n  title = {Learning Single-Criteria Control Knowledge for\n\n                  Multi-Criteria Planning},\n\n  booktitle = {Proceedings of the AIPS-02 Workshop on Planning and\n\n                  Scheduling with Multiple Criteria},\n\n  editor = {Brian Drabble and Jana Koehler and Ioannis Refanidis},\n\n  year = {2002},\n\n  address = {Toulouse (France)},\n\n  cicyt = {workshops},\n\n  month = {April},\n\n  pages = {35--40},\n\n  url = {aips02-workshop.ps.gz},\n\n  key = {Planning-Learning},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A knowledge-based approach for business process reengineering, SHAMASH.\n \n \n \n \n\n\n \n Aler, R.; Borrajo, D.; Camacho, D.; and Sierra-Alonso, A.\n\n\n \n\n\n\n Knowledge-Based Systems, 15(8): 473–483. November 2002.\n http://dx.doi.org/10.1016/S0950-7051(02)00032-1\n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{kbs-journal-shamash,\n\n  author = {Ricardo Aler and Daniel Borrajo and David Camacho and Almudena Sierra-Alonso},\n\n  title = {A knowledge-based approach for business process reengineering, {SHAMASH}},\n\n  journal = {Knowledge-Based Systems},\n\n  publisher = {Elsevier},\n\n  year = {2002},\n\n  url = {http://hdl.handle.net/10016/5697},\n\n  key = {Organisations modelling},\n\n  volume = {15},\n\n  number = {8},\n\n  month = {November},\n\n  cicyt = {revista},\n\n  jcr = {Q3, 2002: 0.384 (48/74)},\n\n  optjcr = {2004: 0.645 (44/78), 2005: 0.696 (50/78), 2006: 0.576 (63/85), 2007: 0.574 (70/93)},\n\n  pages = {473--483},\n\n  note = {http://dx.doi.org/10.1016/S0950-7051(02)00032-1}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n MAPWEB: Cooperation between Planning Agents and Web Agents.\n \n \n \n \n\n\n \n Camacho, D.; Molina, J. M.; Borrajo, D.; and Aler, R.\n\n\n \n\n\n\n Information & Security. An International Journal. Special Issue on Multi-Agent Technologies, 8(2): 209-238. 2002.\n \n\n\n\n
\n\n\n\n \n \n $\"MAPWEB:$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{is-journal,\n\n  author = {David Camacho and José Manuel Molina and Daniel Borrajo and\n\n                  Ricardo Aler},\n\n  title = {{MAPWEB}: {C}ooperation between Planning Agents and Web\n\n                  Agents},\n\n  journal = {Information \\& Security. {A}n International Journal. Special Issue on Multi-Agent Technologies},\n\n  year = {2002},\n\n  url = {http://hdl.handle.net/10016/5792},\n\n  publisher = {ISN (International Relations and Security Network)},\n\n  key = {Planning-Web},\n\n  volume = {8},\n\n  number = {2},\n\n  pages = {209-238},\n\n  cicyt = {revista-noJCR},\n\n  optannote = {ISSN 1311-1493}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Context Vector Model for Information Retrieval.\n \n \n \n \n\n\n \n Billhardt, H.; Borrajo, D.; and Maojo, V.\n\n\n \n\n\n\n Journal of American Society for Information Science and Technology, 53(3): 236–249. 2002.\n http://dx.doi.org/10.1002/asi.10032\n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jasist02,\n\n  author = {Holger Billhardt and Daniel Borrajo and Victor Maojo},\n\n  title = {A Context Vector Model for Information Retrieval},\n\n  journal = {Journal of American Society for Information Science and Technology},\n\n  year = {2002},\n\n  month = {},\n\n  url = {http://hdl.handle.net/10016/6790},\n\n  key = {Learning-Information Retrieval},\n\n  publisher = {John Wiley \\& Sons},\n\n  volume = {53},\n\n  number = {3},\n\n  cicyt = {revista},\n\n  jcr = {Q1, Categoría: Computer Science, Information Systems. 2002: 1.773 (9/77)},\n\n  optjcr = {Categoría: Computer Science, Information Systems. 2002: 1.773 (9/77), 2004: 2.086 (12/78), 2005: 1.583 (20/83), 2006: 1.555 (22/87), 2007: 1.436 (29/92)},\n\n  pages = {236--249},\n\n  annote = {ISSN: 1532-2882},\n\n  note = {http://dx.doi.org/10.1002/asi.10032}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Heuristic Search-Based Stacking of Classifiers.\n \n \n \n \n\n\n \n Ledezma, A.; Aler, R.; and Borrajo, D.\n\n\n \n\n\n\n Heuristic and Optimization for Knowledge Discovery, pages 54–67. Sarker, R.; Abbass, H.; and Newton, C., editor(s). Idea Group Publishing, 2002.\n \n\n\n\n
\n\n\n\n \n \n $\"Heuristic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inbook{book-data-mining,\n\n  author = {Agapito Ledezma and Ricardo Aler and Daniel Borrajo},\n\n  title = {Heuristic and Optimization for Knowledge Discovery},\n\n  chapter = {Heuristic Search-Based Stacking of Classifiers},\n\n  publisher = {Idea Group Publishing},\n\n  cicyt = {capitulos},\n\n  year = {2002},\n\n  editor = {Ruhul Sarker and Hussein Abbass and Charles Newton},\n\n  pages = {54--67},\n\n  url = {book-data-mining.pdf},\n\n  key = {Multi-Agent Learning}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Automatic Finding of Good Classifiers Following a Biologically Inspired Metaphor.\n \n \n \n\n\n \n Fernández, F.; and Isasi, P.\n\n\n \n\n\n\n Computing and Informatics, 21(3): 205-220. 2002.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{fernandez02c,\n\n  author = {Fernando Fern\\'andez and Pedro Isasi},\n\n  title = {Automatic Finding of Good Classifiers Following a Biologically Inspired Metaphor},\n\n  journal = {Computing and Informatics},\n\n  year = {2002},\n\n  volume = {21},\n\n  number = {3},\n\n  key = {Reactive},\n\n  cicyt = {revista},\n\n  pages = {205-220}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Telemedicine as a tool for intensive management of diabetes: the DIABTel experience.\n \n \n \n\n\n \n Gómez, E.; Hernando, M.; García, A.; Pozo, F. D.; Cermeño, J.; Corcoy, R.; Brugués, E.; and Leiva, A. D.\n\n\n \n\n\n\n Computers Methods and Programs in Biomedicine, 69(2): 163-177. 2002.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Gomez02,\n\n  author = {E.J. Gómez and M.E. Hernando and  A. García and F. Del Pozo and J. Cermeño and R. Corcoy and E. Brugués and A. De Leiva},\n\n  title = {Telemedicine as a tool for intensive management of diabetes: the DIABTel experience},\n\n  year = {2002},\n\n  journal = {Computers Methods and Programs in Biomedicine},\n\n  pages = {163-177},\n\n  volume = {69},\n\n  number = {2},\n\n  key = {Other},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n A Multi-Access Shared Workspace for Diabetes Management.\n \n \n \n\n\n \n Aguilera, E. J. G.; Garcia, A.; Hernando, E.; García, M.; and del Pozo, F.\n\n\n \n\n\n\n Telemedicine Journal and e-Health, 8(2): 247. 2002.\n \n\n\n\n
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@article{Gomez02b,\n\n  author = {Enrique J. Gómez Aguilera and Angel Garcia and Elena Hernando and Miguel García and Francisco del Pozo},\n\n  title = {A Multi-Access Shared Workspace for Diabetes Management},\n\n  year = {2002},\n\n  journal = {Telemedicine Journal and e-Health},\n\n  pages = {247},\n\n  volume = {8},\n\n  number = {2},\n\n  key = {Other},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Una implementación general de los modelos fundamentales de razonamiento inteligente.\n \n \n \n \n\n\n \n Linares López, C.; and Gómez, A.\n\n\n \n\n\n\n In Proceedings of the Nineth Conference of the Spanish Association for Artificial Intelligence (CAEPIA'01), volume II, pages 1239–1248, Gijón, Spain, November 2001. \n \n\n\n\n
\n\n\n\n \n \n $\"Una$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c.gomez.a:una,\n  author\t= {Carlos {Linares L\\'opez} and Asunci\\'on G\\'omez},\n  title\t\t= {Una implementaci\\'on general de los modelos fundamentales\n\t\t  de razonamiento inteligente},\n  booktitle\t= {Proceedings of the Nineth Conference of the Spanish\n\t\t  Association for Artificial Intelligence (CAEPIA'01)},\n  pages\t\t= {1239--1248},\n  year\t\t= 2001,\n  volume\t= {II},\n  address\t= {Gij\\'on, Spain},\n  month\t\t= nov,\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/ttia01.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Caracterización de los modelos de búsqueda de un agente con descripciones generalizadas de los nodos origen y destino.\n \n \n \n \n\n\n \n Linares López, C.\n\n\n \n\n\n\n Ph.D. Thesis, Facultad de Informática. Universidad Politécnica de Madrid, December 2001.\n \n\n\n\n
\n\n\n\n \n \n $\"Caracterización$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@PhDThesis{\t  linares-lopez.c:caracterizacion,\n  author\t= {Carlos {Linares L\\'opez}},\n  title\t\t= {Caracterizaci\\'on de los modelos de b\\'usqueda de un\n\t\t  agente con descripciones generalizadas de los nodos origen\n\t\t  y destino},\n  school\t= {Facultad de Informática. Universidad Polit\\'ecnica de\n\t\t  Madrid},\n  year\t\t= 2001,\n  month\t\t= dec,\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/phd.tar.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Learning in large cooperative multi-robot domains.\n \n \n \n \n\n\n \n Fernández, F.; and Parker, L.\n\n\n \n\n\n\n International Journal of Robotics and Automation, 16(4). 2001.\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Fernandez2001,\nabstract = {The development of mechanisms that enable robot teams to autonomously generate cooperative behaviours is one of the most interesting issues in distributed and autonomous robotic systems. The authors study the application of reinforcement learning techniques to robot teams, which enable the robot to learn cooperative behaviours based only on local information. The VQQL technique is applied both to learn a state-space representation of the environment and to learn a correct behaviour. The Cooperative Multi-robot Observation of Multiple Moving Targets (CMOMMT) application is used as a well-known domain in the robotics field, and results, compared with previous work, reveal improved performance.},\nauthor = {Fern{\\'{a}}ndez, F. and Parker, L.E.},\nfile = {:home/fernando/papers/tmp/ijra01.pdf:pdf},\nissn = {08268185},\njournal = {International Journal of Robotics and Automation},\nkeywords = {Cooperative robotics,Multi-robot systems,Reinforcement learning,State-space representation},\nnumber = {4},\ntitle = {{Learning in large cooperative multi-robot domains}},\nurl = {http://www.actapress.com/Content{\\_}Of{\\_}Journal.aspx?JournalID=62},\nvolume = {16},\nyear = {2001}\n}\n

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\n \n\n \n \n \n \n \n \n Planning-based Generation of Process Models.\n \n \n \n \n\n\n \n Rodríguez-Moreno, M. D.; Borrajo, D.; and Meziat, D.\n\n\n \n\n\n\n In McCluskey, L.; and Milani, A., editor(s), Proceedings of the ECP-01/PLANET Workshop on Automated Planning and Scheduling Technologies in New Methods of Electronic, Mobile and Collaborative Work, pages 22–34, Toledo (Spain), September 2001. \n \n\n\n\n
\n\n\n\n \n \n $\"Planning-based$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ecp01-workshop,\n\n  author = {María Dolores Rodríguez-Moreno and Daniel Borrajo and Daniel\n\n                  Meziat},\n\n  title = {Planning-based Generation of Process Models},\n\n  booktitle = {Proceedings of the ECP-01/PLANET Workshop on Automated\n\n                  Planning and Scheduling Technologies in New Methods of\n\n                  Electronic, Mobile and Collaborative Work},\n\n  editor = {Lee McCluskey and Alfredo Milani},\n\n  year = {2001},\n\n  cicyt = {workshops},\n\n  key = {Organisations modelling},\n\n  url = {ecp01-workshop.pdf.gz},\n\n  address = {Toledo (Spain)},\n\n  month = {September},\n\n  pages = {22--34},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Empirical Study of a Stacking State-space.\n \n \n \n \n\n\n \n Ledezma, A.; Aler, R.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the Thirteenth IEEE International Conference on Tools with Artificial Intelligence, pages 210-217, Dallas, Texas, November 2001. IEEE Computer Society\n http://dx.doi.org/10.1109/ICTAI.2001.974467\n\n\n\n
\n\n\n\n \n \n $\"Empirical$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ictai01-stacking,\n\n  author = {Agapito Ledezma and Ricardo Aler and Daniel Borrajo},\n\n  title = {Empirical Study of a Stacking State-space},\n\n  booktitle = {Proceedings of the Thirteenth IEEE International Conference on Tools with Artificial Intelligence},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  cicyt = {congresos},\n\n  year = {2001},\n\n  url = {http://hdl.handle.net/10016/6100},\n\n  publisher = {IEEE Computer Society},\n\n  address = {Dallas, Texas},\n\n  key = {Multi-Agent Learning},\n\n  month = {November},\n\n  pages = {210-217},\n\n  jcr = {B},\n\n  note = {http://dx.doi.org/10.1109/ICTAI.2001.974467}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Quality-based Learning for Planning.\n \n \n \n \n\n\n \n Borrajo, D.; Vegas, S.; and Veloso, M.\n\n\n \n\n\n\n In , editor(s), Working notes of the IJCAI'01 Workshop on Planning with Resources, pages 9–17, Seattle, WA (USA), August 2001. IJCAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Quality-based$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ijcai01,\n\n  author = {Daniel Borrajo and Sira Vegas and Manuela Veloso},\n\n  title = {Quality-based Learning for Planning},\n\n  booktitle = {Working notes of the IJCAI'01 Workshop on Planning with\n\n                  Resources},\n\n  editor = {},\n\n  year = {2001},\n\n  url = {ijcai01.ps.gz},\n\n  cicyt = {workshops},\n\n  publisher = {IJCAI Press},\n\n  address = {Seattle, WA (USA)},\n\n  month = {August},\n\n  key = {Planning-Learning},\n\n  pages = {9--17},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Grammars for Learning Control Knowledge with GP.\n \n \n \n \n\n\n \n Aler, R.; Isasi, P.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the Congress on Evolutionary Computation (CEC'01), volume 2, pages 1220–1227, Seoul (Korea), May 2001. IEEE Society\n \n\n\n\n
\n\n\n\n \n \n $\"Grammars$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{cec01,\n\n  author = {Ricardo Aler and Pedro Isasi and Daniel Borrajo},\n\n  title = {Grammars for Learning Control Knowledge with {GP}},\n\n  booktitle = {Proceedings of the Congress on Evolutionary Computation (CEC'01)},\n\n  volume = {2},\n\n  year = {2001},\n\n  url = {http://hdl.handle.net/10016/4028},\n\n  publisher = {IEEE Society},\n\n  address = {Seoul (Korea)},\n\n  month = {May},\n\n  cicyt = {congresos},\n\n  key = {Planning-Learning},\n\n  pages = {1220--1227},\n\n  jcr = {A}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Intelligent Travel Planning: A Multiagent Planning System to Solve Web Problems in the e-Tourism Domain.\n \n \n \n \n\n\n \n Camacho, D.; Borrajo, D.; and Molina, J. M.\n\n\n \n\n\n\n Journal of Autonomous Agents and Multi-Agent Systems, 4(4): 387–392. December 2001.\n http://dx.doi.org/10.1023/A:1012767210241\n\n\n\n
\n\n\n\n \n \n $\"Intelligent$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{autonomous-agents,\n\n  author = {David Camacho and Daniel Borrajo and José Manuel Molina},\n\n  title = {Intelligent Travel Planning: {A} Multiagent Planning System\n\n                  to Solve Web Problems in the e-Tourism Domain},\n\n  journal = {Journal of Autonomous Agents and Multi-Agent Systems},\n\n  year = {2001},\n\n  url = {http://hdl.handle.net/10016/6788},\n\n  key = {Planning-Web},\n\n  volume = {4},\n\n  number = {4},\n\n  publisher = {Kluwer Academic Publishers},\n\n  month = {December},\n\n  cicyt = {revista},\n\n  jcr = {Entró en 2002: 1.129 (19/74)},\n\n  optjcr = {2004: 1.447 (22/78), 2005: 2.605 (8/79), 2006: 1.974 (17/85), 2007: 1.340 (34/93)},\n\n  pages = {387--392},\n\n  note = {http://dx.doi.org/10.1023/A:1012767210241}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n \\sc ABC$^{2}$ An Agenda Based Multi-Agent Model for Robots Control and Cooperation.\n \n \n \n \n\n\n \n Matellán, V.; and Borrajo, D.\n\n\n \n\n\n\n Journal of Intelligent and Robotic Systems, 32(1): 93-114. October 2001.\n http://dx.doi.org/10.1023/A:1008134010576\n\n\n\n
\n\n\n\n \n \n $\"\\sc$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jirs01,\n\n  author = {Vicente Matell\\'{a}n and Daniel Borrajo},\n\n  title = {{\\sc ABC$^{2}$} An Agenda Based Multi-Agent Model for Robots Control and Cooperation},\n\n  journal = {Journal of Intelligent and Robotic Systems},\n\n  publisher = {Springer Verlag},\n\n  year = {2001},\n\n  url = {http://hdl.handle.net/10016/6769},\n\n  volume = {32},\n\n  number = {1},\n\n  key = {Reactive},\n\n  month = {October},\n\n  cicyt = {revista},\n\n  jcr = {Q3, 2001: 0.298 (55/72)},\n\n  optjcr = {2004: 0.254 (69/78), 2005: 0.219 (72/79), 2006: 0.265 (79/85), 2007: 0.459 (75/93)},\n\n  pages = {93-114},\n\n  note = {http://dx.doi.org/10.1023/A:1008134010576},\n\n  annote = {.// En Categoría Robotics: 2007 (10/13)}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Learning to Solve Planning Problems Efficiently by Means of Genetic Programming.\n \n \n \n \n\n\n \n Aler, R.; Borrajo, D.; and Isasi, P.\n\n\n \n\n\n\n Evolutionary Computation, 9(4): 387–420. 2001.\n http://dx.doi.org/10.1162/10636560152642841\n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ec-journal,\n\n  author = {Ricardo Aler and Daniel Borrajo and Pedro Isasi},\n\n  title = {Learning to Solve Planning Problems  Efficiently by Means of\n\n                  Genetic Programming},\n\n  journal = {Evolutionary Computation},\n\n  publisher = {MIT Press},\n\n  year = {2001},\n\n  url = {http://hdl.handle.net/10016/4087},\n\n  volume = {9},\n\n  number = {4},\n\n  key = {Planning-Learning},\n\n  cicyt = {revista},\n\n  jcr = {Entró en 2003: 2.395 (13/77)},\n\n  optjcr = {2004: 3.206 (7/78), 2005: 1.568 (27/79), 2006: 1.325 (32/85), 2007: 1.575 (24/93), 2008: 3.000 (13/94)},\n\n  pages = {387--420},\n\n  note = {http://dx.doi.org/10.1162/10636560152642841}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Telemedicine may assist diabetic subjects to improve metabolic outcome and promote patients empowerment.\n \n \n \n\n\n \n Brugues, E.; Cermeno, J.; Corcoy, R.; Hernando, E.; Gomez-Aguilera, E.; Garcia, A.; and de Leiva, A.\n\n\n \n\n\n\n Diabetologia, 44(1): 59A. 2001.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Brugues01,\n\n  author = {E. Brugues and J. Cermeno and R. Corcoy and E. Hernando and E. Gomez-Aguilera and A. Garcia and A. de Leiva},\n\n  title = {Telemedicine may assist diabetic subjects to improve metabolic outcome and promote patients empowerment},\n\n  year = {2001},\n\n  journal = {Diabetologia},\n\n  pages = {59A},\n\n  volume = {44},\n\n  number = {1},\n\n  key = {Other},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Búsqueda bidireccional en dominios discretos y continuos.\n \n \n \n \n\n\n \n Linares López, C.\n\n\n \n\n\n\n Revista Iberoamericana de Inteligencia Artificial, Verano(10): 26–42. 2000.\n \n\n\n\n
\n\n\n\n \n \n $\"Búsqueda$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@Article{\t  linares-lopez.c:busqueda,\n  author\t= {Carlos {Linares L\\'opez}},\n  title\t\t= {B\\'usqueda bidireccional en dominios discretos y\n\t\t  continuos},\n  journal\t= {Revista Iberoamericana de Inteligencia Artificial},\n  year\t\t= {2000},\n  volume\t= {Verano},\n  number\t= {10},\n  pages\t\t= {26--42},\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/aepia-00.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Using the general next bit predictor like an evaluation criteria.\n \n \n \n \n\n\n \n Hernández, J. C.; Sierra, J. M.; Mex-Perera, C.; Borrajo, D.; Ribagorda, A.; and Isasi, P.\n\n\n \n\n\n\n In Proceedings of the NESSIE workshop (New European Schemes for Signature, Integrity, and Encryption), Leuven (Belgium), November 2000. \n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{nessie00,\n\n  author = {Julio César Hernández and José María Sierra and\n\n                  Carlos Mex-Perera and Daniel Borrajo and Arturo Ribagorda and\n\n                  Pedro Isasi},\n\n  title = {Using the general next bit predictor like an evaluation\n\n                  criteria},\n\n  booktitle = {Proceedings of the NESSIE workshop (New European Schemes for\n\n                  Signature, Integrity, and Encryption)},\n\n  opteditor = {},\n\n  optvolume = {},\n\n  optnumber = {},\n\n  optseries = {},\n\n  year = {2000},\n\n  url = {nessie00.ps.gz},\n\n  optorganization = {},\n\n  optpublisher = {},\n\n  cicyt = {workshops},\n\n  address = {Leuven (Belgium)},\n\n  month = {November},\n\n  key = {Other},\n\n  optpages = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Knowledge Representation Issues in Control Knowledge Learning.\n \n \n \n \n\n\n \n Aler, R.; Borrajo, D.; and Isasi, P.\n\n\n \n\n\n\n In Langley, P., editor(s), Proceedings of the Seventeenth International Conference on Machine Learning, ICML'00, pages 1–8, Stanford, CA (USA), June-July 2000. \n \n\n\n\n
\n\n\n\n \n \n $\"Knowledge$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icml00,\n\n  author = {Ricardo Aler and Daniel Borrajo and Pedro Isasi},\n\n  title = {Knowledge Representation Issues in Control Knowledge Learning},\n\n  booktitle = {Proceedings of the Seventeenth International Conference on\n\n                  Machine Learning, ICML'00},\n\n  editor = {Pat Langley},\n\n  year = {2000},\n\n  cicyt = {congresos-buenos},\n\n  url = {http://hdl.handle.net/10016/4151},\n\n  address = {Stanford, CA (USA)},\n\n  month = {June-July},\n\n  key = {Planning-Learning},\n\n  pages = {1--8},\n\n  jcr = {A*}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n GP fitness functions to evolve heuristics for planning.\n \n \n \n \n\n\n \n Aler, R.; Borrajo, D.; and Isasi, P.\n\n\n \n\n\n\n In Middendorf, M., editor(s), Evolutionary Methods for AI Planning, pages 189-195, Las Vegas, NV (USA), July 2000. \n \n\n\n\n
\n\n\n\n \n \n $\"GP$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{gecco00,\n\n  author = {Ricardo Aler and Daniel Borrajo and Pedro Isasi},\n\n  title = {{GP} fitness functions to evolve heuristics for planning},\n\n  booktitle = {Evolutionary Methods for AI Planning},\n\n  annote = {Proceedings of the GECCO'00 Workshop Program. Workshop  on\n\n                  EC for AI Planning},\n\n  editor = {Martin Middendorf},\n\n  year = {2000},\n\n  url = {gecco00.ps.gz},\n\n  address = {Las Vegas, NV (USA)},\n\n  month = {July},\n\n  cicyt = {workshops},\n\n  key = {Planning-Learning},\n\n  pages = {189-195},\n\n  jcr = {B}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Learning Models of Other Agents.\n \n \n \n \n\n\n \n Aler, R.; Borrajo, D.; Galván, I.; and Ledezma, A.\n\n\n \n\n\n\n In Proceedings of the Agents-00/ECML-00 Workshop on Learning Agents, pages 1–5, Barcelona, Spain, 2000. \n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{agents00-models,\n\n  author = {Ricardo Aler and Daniel Borrajo and Inés Galván and Agapito\n\n                  Ledezma},\n\n  title = {Learning Models of Other Agents},\n\n  booktitle = {Proceedings of the Agents-00/ECML-00 Workshop on Learning\n\n                  Agents},\n\n  pages = {1--5},\n\n  organization = {},\n\n  month = {},\n\n  cicyt = {workshops},\n\n  key = {Multi-Agent Learning},\n\n  address = {Barcelona, Spain},\n\n  year = {2000},\n\n  url = {agents00.pdf},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n \\sc VQQL. Applying Vector Quantization to Reinforcement Learning.\n \n \n \n \n\n\n \n Fernández, F.; and Borrajo, D.\n\n\n \n\n\n\n In M. Veloso, E. P.; and Kitano, H., editor(s), RoboCup-99: Robot Soccer World Cup III, volume 1856, of Lecture Notes in Computer Science, pages 292–303, Stockholm (Sweden), 2000. Springer-Verlag\n http://dx.doi.org/10.1007/3-540-45327-X_24\n\n\n\n
\n\n\n\n \n \n $\"\\sc$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{robocup00,\n\n  author = {Fernando Fernández and Daniel Borrajo},\n\n  title = {{\\sc VQQL}. {A}pplying Vector Quantization to Reinforcement Learning},\n\n  booktitle = {RoboCup-99: Robot Soccer World Cup III},\n\n  publisher = {Springer-Verlag},\n\n  series = {Lecture Notes in Computer Science},\n\n  cicyt = {lncs},\n\n  volume = {1856},\n\n  editor = {M. Veloso, E. Pagello and H. Kitano},\n\n  year = {2000},\n\n  url = {http://hdl.handle.net/10016/7369},\n\n  key = {Reactive},\n\n  address = {Stockholm (Sweden)},\n\n  annote = {ISBN: 3-540-41043-0},\n\n  pages = {292--303},\n\n  jcr = {B},\n\n  note = {http://dx.doi.org/10.1007/3-540-45327-X_24}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n An Integrated Approach of Learning, Planning, and Execution.\n \n \n \n \n\n\n \n García-Martínez, R.; and Borrajo, D.\n\n\n \n\n\n\n Journal of Intelligent and Robotic Systems, 29(1): 47–78. September 2000.\n \n\n\n\n
\n\n\n\n \n \n $\"An$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jirs00,\n\n  author = {Ramón García-Martínez and Daniel Borrajo},\n\n  title = {An Integrated Approach of Learning, Planning, and Execution},\n\n  journal = {Journal of Intelligent and Robotic Systems},\n\n  publisher = {Springer Verlag},\n\n  year = {2000},\n\n  url = {jirs00.ps.gz},\n\n  volume = {29},\n\n  number = {1},\n\n  month = {September},\n\n  key = {Reactive},\n\n  cicyt = {revista},\n\n  jcr = {Q4, 2000: 0.083 (68/71)},\n\n  optjcr = {2004: 0.254 (69/78), 2005: 0.219 (72/79), 2006: 0.265 (79/85), 2007: 0.459 (75/93)},\n\n  pages = {47--78},\n\n  annote = {.// En Categoría Robotics: 2007 (10/13)}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using Term Co-occurrence Data for Document Indexing and Retrieval.\n \n \n \n \n\n\n \n Billhardt, H.; Borrajo, D.; and Maojo, V.\n\n\n \n\n\n\n In Proceedings of the BCS-IRSG 22nd Annual Colloquium on Information Retrieval Research (IRSG2000), pages 105–117, Cambridge, England, April 2000. \n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{irsg00,\n\n  author = {Holger Billhardt and Daniel Borrajo and Victor Maojo},\n\n  title = {Using Term Co-occurrence Data for Document Indexing and\n\n                  Retrieval},\n\n  booktitle = {Proceedings of the BCS-IRSG 22nd Annual Colloquium on\n\n                  Information Retrieval Research (IRSG2000)},\n\n  year = {2000},\n\n  url = {irsg00.pdf},\n\n  cicyt = {congresos},\n\n  key = {Learning-Information Retrieval},\n\n  address = {Cambridge, England},\n\n  month = {April},\n\n  pages = {105--117},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Búsqueda bidireccional en dominios discretos y continuos.\n \n \n \n\n\n \n Linares, C.\n\n\n \n\n\n\n Revista Iberoamericana de Inteligencia Artificial, Verano(10): 26–42. 2000.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{linares.c:busqueda,\n\n  author = {Carlos Linares},\n\n  title = {B\\'usqueda bidireccional en dominios discretos y continuos},\n\n  journal = {Revista Iberoamericana de Inteligencia Artificial},\n\n  cicyt = {revista-noJCR},\n\n  year = {2000},\n\n  key = {Search},\n\n  volume = {Verano},\n\n  number = {10},\n\n  pages = {26--42}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Evaluation of the DIABTel telemedicine system.\n \n \n \n\n\n \n Gómez, E.; Hernando, M.; Garcia, A.; Pozo, d. F.; Corcoy, R.; Brugués, E.; Cermeño, J.; and de Leiva, A.\n\n\n \n\n\n\n Diabetes Nutrition and Metabolism, 13(4): 25. 2000.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Gomez00,\n\n  author = {E.J. Gómez and M.E. Hernando and A. Garcia and del F. Pozo and R. Corcoy and E. Brugués and J. Cermeño and A. de Leiva},\n\n  title = {Evaluation of the DIABTel telemedicine system},\n\n  year = {2000},\n\n  journal = {Diabetes Nutrition and Metabolism},\n\n  pages = {25},\n\n  volume = {13},\n\n  number = {4},\n\n  key = {Other},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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\n \n 1999\n \n \n (5)\n \n \n

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\n \n\n \n \n \n \n \n \n SHAMASH a Knowledge-Based System for Business Process Reengineering.\n \n \n \n \n\n\n \n Camacho, D.; Aler, R.; Borrajo, D.; Giráldez, J. I.; and Sierra, A.\n\n\n \n\n\n\n In Richard Ellis, M. M.; and Coenen, F., editor(s), Applications and Innovations in Intelligent Systems VII. Proceedings of Expert Systems 99, The 19th SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence, of BCS Conference Series, pages 269-282, Cambridge, England, December 1999. Springer-Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"SHAMASH$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{es99-shamash,\n\n  author = {David Camacho and Ricardo Aler and Daniel Borrajo and José Ignacio Giráldez and Almudena Sierra},\n\n  title = {SHAMASH a Knowledge-Based System for Business Process Reengineering},\n\n  booktitle = {Applications and Innovations in Intelligent Systems\n\n                  VII. Proceedings of Expert Systems 99, The 19th SGES\n\n                  International Conference on Knowledge Based Systems and\n\n                  Applied Artificial Intelligence},\n\n  editor = {Richard Ellis, Mike Moulton and Frans Coenen},\n\n  series = {BCS Conference Series},\n\n  cicyt = {congresos},\n\n  year = {1999},\n\n  key = {Organisations modelling},\n\n  url = {es99-shamash.ps.gz},\n\n  publisher = {Springer-Verlag},\n\n  address = {Cambridge, England},\n\n  month = {December},\n\n  pages = {269-282},\n\n  annote = {ISBN 1-85233-230-1},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Multistrategy Relational Learning of Heuristics for Problem Solving.\n \n \n \n \n\n\n \n Borrajo, D.; Camacho, D.; and Silva, A.\n\n\n \n\n\n\n In Bramer, M.; Macintosh, A.; and Coenen, F., editor(s), Research and Development in Intelligent Systems XVI. Proceedings of Expert Systems 99, The 19th SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence, of BCS Conference Series, pages 57-71, Cambridge, England, December 1999. Springer-Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Multistrategy$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{es99-ilp,\n\n  author = {Daniel Borrajo and David Camacho and Andrés Silva},\n\n  title = {Multistrategy Relational Learning of Heuristics for Problem\n\n                  Solving},\n\n  booktitle = {Research and Development in Intelligent Systems\n\n                  XVI. Proceedings of Expert Systems 99, The 19th SGES\n\n                  International Conference on Knowledge Based Systems and\n\n                  Applied Artificial Intelligence},\n\n  editor = {Max Bramer and Ann Macintosh and Frans Coenen},\n\n  series = {BCS Conference Series},\n\n  year = 1999,\n\n  cicyt = {congresos},\n\n  url = {es99-ilp.ps.gz},\n\n  publisher = {Springer-Verlag},\n\n  address = {Cambridge, England},\n\n  month = {December},\n\n  pages = {57-71},\n\n  key = {Planning-Learning},\n\n  annote = {ISBN 1-85233-231-X},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Robótica cognoscitiva y aprendizaje automático.\n \n \n \n \n\n\n \n Berlanga, A.; Borrajo, D.; Fernández, F.; García-Martínez, R.; Molina, J. M.; and Sanchis, A.\n\n\n \n\n\n\n In , editor(s), Proceedings of the CAEPIA'99, pages 1–8, Murcia (España), November 1999. \n \n\n\n\n
\n\n\n\n \n \n $\"Robótica$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{caepia99,\n\n  author = {Antonio Berlanga and Daniel Borrajo and Fernando Fernández\n\n                  and Ramón García-Martínez and José M. Molina and Araceli\n\n                  Sanchis},\n\n  title = {Robótica cognoscitiva y aprendizaje automático},\n\n  booktitle = {Proceedings of the CAEPIA'99},\n\n  editor = {},\n\n  year = {1999},\n\n  url = {caepia99.ps.gz},\n\n  publisher = {},\n\n  cicyt = {congresos-nacionales},\n\n  address = {Murcia (España)},\n\n  month = {November},\n\n  key = {Reactive},\n\n  pages = {1--8}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Knowledge-based Modeling of Processes.\n \n \n \n \n\n\n \n Sierra, A.; Aler, R.; and Borrajo, D.\n\n\n \n\n\n\n In , editor(s), Working notes of the IJCAI'99 workshop on Intelligent Workflow and Process Management: The New Frontier for AI in Business, Stockholm, Sweden, July-August 1999. IJCAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Knowledge-based$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ijcai99-shamash,\n\n  author = {Almudena Sierra and Ricardo Aler and Daniel Borrajo},\n\n  title = {Knowledge-based Modeling of Processes},\n\n  booktitle = {Working notes of the IJCAI'99 workshop on Intelligent\n\n                  Workflow and Process Management: The New Frontier for AI in\n\n                  Business},\n\n  editor = {},\n\n  year = {1999},\n\n  key = {Organisations modelling},\n\n  cicyt = {workshops},\n\n  url = {ijcai99-shamash.ps.gz},\n\n  publisher = {IJCAI Press},\n\n  address = {Stockholm, Sweden},\n\n  month = {July-August},\n\n  pages = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Distributed Solution to the PTE Problem.\n \n \n \n \n\n\n \n Giráldez, I.; Elkan, C.; and Borrajo, D.\n\n\n \n\n\n\n In AAAI Spring Symposium on Predictive Toxicology, Stanford, CA (USA), March 1999. AAAI Press\n http://www.aaai.org/Papers/Symposia/Spring/1999/SS-99-01/SS99-01-019.pdf\n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{spring99,\n\n  author = {Ignacio Giráldez and Charles Elkan and Daniel Borrajo},\n\n  title = {A Distributed Solution to the PTE Problem},\n\n  booktitle = {AAAI Spring Symposium on Predictive Toxicology},\n\n  key = {Multi-Agent Learning},\n\n  opteditor = {},\n\n  year = {1999},\n\n  url = {http://hdl.handle.net/10016/7370},\n\n  publisher = {AAAI Press},\n\n  cicyt = {workshops},\n\n  address = {Stanford, CA (USA)},\n\n  month = {March},\n\n  optpages = {},\n\n  note = {http://www.aaai.org/Papers/Symposia/Spring/1999/SS-99-01/SS99-01-019.pdf},\n\n  optannote = {},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n 1998\n \n \n (6)\n \n \n

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\n \n\n \n \n \n \n \n \n Distributed Decision Making in Checkers.\n \n \n \n \n\n\n \n Giráldez, J. I.; and Borrajo, D.\n\n\n \n\n\n\n In van den Herik, H. J.; and Iida, H., editor(s), Computers and Games. Proceedings of the First International Conference, CG'98, of Lecture Notes in Artificial Intelligence, pages 183–194, Tsukuba (Japan), November 1998. Springer-Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Distributed$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{cg98,\n\n  author = {José I. Giráldez and Daniel Borrajo},\n\n  title = {Distributed Decision Making in Checkers},\n\n  booktitle = {Computers and Games. Proceedings of the First International\n\n                  Conference, CG'98},\n\n  publisher = {Springer-Verlag},\n\n  series = {Lecture Notes in Artificial Intelligence},\n\n  cicyt = {lncs},\n\n  number = {LNCS 1558},\n\n  editor = {H. Jaap van den Herik and Hiroyuki Iida},\n\n  year = {1998},\n\n  key = {Multi-Agent Learning},\n\n  url = {http://hdl.handle.net/10016/6850},\n\n  address = {Tsukuba (Japan)},\n\n  month = {November},\n\n  pages = {183--194},\n\n  jcr = {},\n\n  optnote = {http://dx.doi.org/10.1007/3-540-48957-6_11}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Distributed Reinforcement Learning in Multi-Agent Decision Systems.\n \n \n \n \n\n\n \n Giráldez, J. I.; and Borrajo, D.\n\n\n \n\n\n\n In Coelho, H., editor(s), Progress in Artificial Intelligence, Iberamia 98, of Lecture Notes in Artificial Intelligence, pages 148-159, Lisboa, Portugal, October 1998. Springer-Verlag\n http://dx.doi.org/10.1007/3-540-49795-1_13\n\n\n\n
\n\n\n\n \n \n $\"Distributed$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{iberamia98,\n\n  author = {José I. Giráldez and Daniel Borrajo},\n\n  title = {Distributed  Reinforcement  Learning in Multi-Agent Decision\n\n                  Systems},\n\n  booktitle = {Progress in Artificial Intelligence, Iberamia 98},\n\n  publisher = {Springer-Verlag},\n\n  series = {Lecture Notes in Artificial Intelligence},\n\n  cicyt = {lncs},\n\n  number = {LNAI 1484},\n\n  editor = {Helder Coelho},\n\n  year = {1998},\n\n  key = {Multi-Agent Learning},\n\n  url = {http://hdl.handle.net/10016/6908},\n\n  address = {Lisboa, Portugal},\n\n  month = {October},\n\n  pages = {148-159},\n\n  jcr = {},\n\n  note = {http://dx.doi.org/10.1007/3-540-49795-1_13}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Genetic Programming and Deductive-Inductive Learning: A Multistrategy Approach.\n \n \n \n \n\n\n \n Aler, R.; Borrajo, D.; and Isasi, P.\n\n\n \n\n\n\n In Shavlik, J., editor(s), Proceedings of the Fifteenth International Conference on Machine Learning, ICML'98, pages 10-18, Madison, Wisconsin, July 1998. \n \n\n\n\n
\n\n\n\n \n \n $\"Genetic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{icml98,\n\n  author = {Ricardo Aler and Daniel Borrajo and Pedro Isasi},\n\n  title = {Genetic Programming and Deductive-Inductive Learning: {A} Multistrategy Approach},\n\n  booktitle = {Proceedings of the Fifteenth International Conference on Machine Learning, ICML'98},\n\n  editor = {Jude Shavlik},\n\n  year = {1998},\n\n  cicyt = {congresos-buenos},\n\n  url = {http://hdl.handle.net/10016/4152},\n\n  address = {Madison, Wisconsin},\n\n  month = {July},\n\n  key = {Planning-Learning},\n\n  pages = {10-18},\n\n  jcr = {A*}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Genetic Programming of Control Knowledge for Planning.\n \n \n \n \n\n\n \n Aler, R.; Borrajo, D.; and Isasi, P.\n\n\n \n\n\n\n In Simmons, R.; Veloso, M.; and Smith, S., editor(s), Proceedings of the Fourth International Conference on Artificial Intelligence Planning Systems (AIPS-98), pages 137-143, Pittsburgh (EEUU), June 1998. AAAI Press\n Ponencia\n\n\n\n
\n\n\n\n \n \n $\"Genetic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{aips98,\n\n  author = {Ricardo Aler and Daniel Borrajo and Pedro Isasi},\n\n  title = {Genetic Programming of Control Knowledge for Planning},\n\n  booktitle = {Proceedings of the Fourth International Conference on\n\n                  Artificial Intelligence Planning Systems (AIPS-98)},\n\n  editor = {Reid Simmons and Manuela Veloso and Stephen Smith},\n\n  year = {1998},\n\n  url = {aips98.ps.gz},\n\n  publisher = {AAAI Press},\n\n  address = {Pittsburgh (EEUU)},\n\n  month = {June},\n\n  cicyt = {congresos-buenos},\n\n  key = {Planning-Learning},\n\n  pages = {137-143},\n\n  note = {Ponencia},\n\n  jcr = {A* (predecesor de ICAPS)}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Evolving Heuristics for Planning.\n \n \n \n \n\n\n \n Aler, R.; Borrajo, D.; and Isasi, P.\n\n\n \n\n\n\n In V.W. Porto, N. S.; and Eiben, A., editor(s), Evolutionary Programming IV. Seventh International Conference, EP98, of Lecture Notes in Computer Science, pages 745-754, San Diego (EEUU), March 1998. Springer-Verlag\n http://dx.doi.org/10.1007/BFb0040825\n\n\n\n
\n\n\n\n \n \n $\"Evolving$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ep98,\n\n  author = {Ricardo Aler and Daniel Borrajo and Pedro Isasi},\n\n  title = {Evolving Heuristics for Planning},\n\n  booktitle = {Evolutionary Programming IV. Seventh International Conference, EP98},\n\n  editor = {V.W. Porto, N. Saravanan, D. Waagen and A.E. Eiben},\n\n  year = {1998},\n\n  url = {http://hdl.handle.net/10016/4002},\n\n  publisher = {Springer-Verlag},\n\n  address = {San Diego (EEUU)},\n\n  month = {March},\n\n  number = {LNCS 1447},\n\n  pages = {745-754},\n\n  key = {Planning-Learning},\n\n  cicyt = {lncs},\n\n  series = {Lecture Notes in Computer Science},\n\n  jcr = {C},\n\n  note = {http://dx.doi.org/10.1007/BFb0040825}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Using ABC$^2$ in the RoboCup Domain.\n \n \n \n \n\n\n \n Matellán, V.; Borrajo, D.; and Fernández, C.\n\n\n \n\n\n\n In Kitano, H., editor(s), RoboCup-97: Robot Soccer World Cup I, of Lecture Notes in Artificial Intelligence, pages 475-483, Nagoya (Japan), 1998. Springer-Verlag\n http://dx.doi.org/10.1007/3-540-64473-3_85\n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{robocup98,\n\n  author = {Vicente Matellán and Daniel Borrajo and Camino Fernández},\n\n  title = {Using {ABC}$^2$ in the RoboCup Domain},\n\n  booktitle = {RoboCup-97: Robot Soccer World Cup I},\n\n  publisher = {Springer-Verlag},\n\n  series = {Lecture Notes in Artificial Intelligence},\n\n  cicyt = {lncs},\n\n  number = {1395},\n\n  annote = {ISBN 3-540-64473-3},\n\n  address = {Nagoya (Japan)},\n\n  editor = {Hiroaki Kitano},\n\n  year = {1998},\n\n  url = {http://hdl.handle.net/10016/6929},\n\n  key = {Reactive},\n\n  pages = {475-483},\n\n  jcr = {B},\n\n  note = {http://dx.doi.org/10.1007/3-540-64473-3_85}\n\n}\n\n\n\n

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\n \n 1997\n \n \n (6)\n \n \n

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\n \n\n \n \n \n \n \n \n Games: A New Scenario for Software And Knowledge Reuse.\n \n \n \n \n\n\n \n Linares López, C.; Estévez, U. D.; Gómez, A.; and Sánchez, L. M.\n\n\n \n\n\n\n In Proceedings of the Nineth International Conference on Software Engineering and Knowlege Engineering (SEKE'97), pages 208–215, Madrid, Spain, June 1997. \n \n\n\n\n
\n\n\n\n \n \n $\"Games:$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c.estevez.ud.ea:games,\n  author\t= "Carlos {Linares L\\'opez} and Ubaldo David Est\\'evez and\n\t\t  Asunci\\'on G\\'omez and Luis Manuel Sánchez",\n  title\t\t= "Games: A New Scenario for Software And Knowledge Reuse",\n  booktitle\t= "Proceedings of the Nineth International Conference on\n\t\t  Software Engineering and Knowlege Engineering (SEKE'97)",\n  year\t\t= 1997,\n  month\t\t= jun,\n  pages\t\t= "208--215",\n  address\t= "Madrid, Spain",\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/seke-97.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n BHFFA$^*$: Un nuevo algoritmo admisible de búsqueda bidireccional.\n \n \n \n \n\n\n \n Linares López, C.; and Gómez, A.\n\n\n \n\n\n\n In Proceedings of the Seventh Conference of the Spanish Association for Artificial Intelligence (CAEPIA'97), pages 705–714, Málaga, Spain, November 1997. \n \n\n\n\n
\n\n\n\n \n \n $\"BHFFA$^*$:$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@InProceedings{\t  linares-lopez.c.gomez.a:bhffa,\n  author\t= {Carlos {Linares L\\'opez} and Asunci\\'on G\\'omez},\n  title\t\t= {{BHFFA}$^*$: Un nuevo algoritmo admisible de b\\'usqueda\n\t\t  bidireccional},\n  booktitle\t= {Proceedings of the Seventh Conference of the Spanish\n\t\t  Association for Artificial Intelligence (CAEPIA'97)},\n  pages\t\t= {705--714},\n  year\t\t= 1997,\n  month\t\t= nov,\n  address\t= {Málaga, Spain},\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/bhffa.pdf.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Algoritmos de búsqueda de un agente en dominios discretos y continuos.\n \n \n \n \n\n\n \n Linares López, C.\n\n\n \n\n\n\n Master's thesis, Facultad de Informática. Universidad Politécnica de Madrid, May 1997.\n \n\n\n\n
\n\n\n\n \n \n $\"Algoritmos$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@MastersThesis{\t  linares-lopez.c:algoritmos,\n  author\t= "Carlos {Linares L\\'opez}",\n  title\t\t= "Algoritmos de b\\'usqueda de un agente en dominios\n\t\t  discretos y continuos",\n  school\t= "Facultad de Informática. Universidad Polit\\'ecnica de\n\t\t  Madrid",\n  year\t\t= 1997,\n  month\t\t= may,\n  url\t\t= {http://www.plg.inf.uc3m.es/~clinares/download/papers/msc.tar.gz}\n\t\t  \n}\n\n

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\n \n\n \n \n \n \n \n \n Planning, Learning, and Executing in Autonomous Systems.\n \n \n \n \n\n\n \n García-Martínez, R.; and Borrajo, D.\n\n\n \n\n\n\n In Steel, S., editor(s), Recent Advances in AI Planning. 4th European Conference on Planning, ECP'97, of Lecture Notes in Artificial Intelligence, pages 208-220, Toulouse, France, September 1997. Springer-Verlag\n http://dx.doi.org/10.1007/3-540-63912-8_87\n\n\n\n
\n\n\n\n \n \n $\"Planning,$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ecp97,\n\n  author = {Ramón García-Martínez and Daniel Borrajo},\n\n  title = {Planning, Learning, and Executing in Autonomous Systems},\n\n  booktitle = {Recent Advances in AI Planning. 4th European\n\n                  Conference on Planning, ECP'97},\n\n  editor = {Sam Steel},\n\n  year = {1997},\n\n  url = {http://hdl.handle.net/10016/6843},\n\n  note = {http://dx.doi.org/10.1007/3-540-63912-8_87},\n\n  publisher = {Springer-Verlag},\n\n  address = {Toulouse, France},\n\n  month = {September},\n\n  pages = {208-220},\n\n  number = {LNAI 1348},\n\n  key = {Reactive},\n\n  cicyt = {congresos-buenos},\n\n  series = {Lecture Notes in Artificial Intelligence},\n\n  jcr = {A* (predecesor de ICAPS)}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Computational Approach to George Boole's Discovery of Mathematical Logic.\n \n \n \n \n\n\n \n de Ledesma, L.; Pérez, A.; Borrajo, D.; and Laita, L. M.\n\n\n \n\n\n\n Artificial Intelligence Journal, 91(2): 281-308. April 1997.\n http://dx.doi.org/10.1016/S0004-3702(97)00017-9\n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aij-boole,\n\n  author = {Luis de Ledesma and Aurora Pérez and Daniel Borrajo and Luis M. Laita},\n\n  title = {A Computational Approach to {G}eorge {B}oole's Discovery of {M}athematical {L}ogic},\n\n  journal = {Artificial Intelligence Journal},\n\n  publisher = {Elsevier},\n\n  volume = {91},\n\n  number = {2},\n\n  pages = {281-308},\n\n  month = {April},\n\n  year = {1997},\n\n  key = {Other},\n\n  cicyt = {revista},\n\n  jcr = {Q1, 1997: 1.683 (2/54)},\n\n  optjcr = {2004: 3.570 (4/78), 2005: 2.368 (7/79), 2006: 2.271 (12/85), 2007: 3.008 (6/93)},\n\n  note = {http://dx.doi.org/10.1016/S0004-3702(97)00017-9},\n\n  url = {http://hdl.handle.net/10016/6768}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Lazy Incremental Learning of Control Knowledge for Efficiently Obtaining Quality Plans.\n \n \n \n \n\n\n \n Borrajo, D.; and Veloso, M.\n\n\n \n\n\n\n AI Review Journal. Special Issue on Lazy Learning, 11(1-5): 371-405. February 1997.\n Also in the book \"Lazy Learning\", David Aha (ed.), Kluwer Academic Publishers, May 1997, ISBN 0-7923-4584-3\n\n\n\n
\n\n\n\n \n \n $\"Lazy$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aireview,\n\n  author = {Daniel Borrajo and Manuela Veloso},\n\n  title = {Lazy Incremental Learning of Control Knowledge for\n\n\t\t  Efficiently Obtaining Quality Plans},\n\n  journal = {AI Review Journal. Special Issue on Lazy Learning},\n\n  publisher = {Springer Verlag},\n\n  volume = {11},\n\n  number = {1-5},\n\n  pages = {371-405},\n\n  month = {February},\n\n  year = {1997},\n\n  cicyt = {revista},\n\n  jcr = {Q4, 1997: 0.058 (49/54)},\n\n  optjcr = {2004: 0.562 (53/78), 2005: 0.868 (41/79), 2006: 0.694 (58/85), 2007: 0.634 (63/93)},\n\n  url = {http://hdl.handle.net/10016/6842},\n\n  key = {Planning-Learning},\n\n  annote = {http://dx.doi.org/10.1023/A:1006549800144},\n\n  note = {Also in the book "Lazy Learning", David Aha (ed.), Kluwer\n\n                  Academic Publishers, May 1997, ISBN 0-7923-4584-3}\n\n}\n\n\n\n

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\n \n 1995\n \n \n (2)\n \n \n

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\n \n\n \n \n \n \n \n \n Theory-driven historical discovery: Boole's abstract formalization of Logic.\n \n \n \n \n\n\n \n de Ledesma, L.; Pérez, A.; Borrajo, D.; and Laita, L. M.\n\n\n \n\n\n\n In Working notes of the AAAI Spring Series Symposium 1995 on Systematic Methods of Scientific Discovery, pages 60-65, Stanford, CA (USA), March 1995. AAAI\n \n\n\n\n
\n\n\n\n \n \n $\"Theory-driven$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{spring95,\n\n  author = {Luis de Ledesma and Aurora Pérez and Daniel Borrajo \n\n\tand Luis M. Laita},\n\n  title = {Theory-driven historical discovery: Boole's abstract \n\n          formalization of Logic},\n\n  booktitle = {Working notes of the AAAI Spring Series Symposium\n\n\t1995 on Systematic Methods of Scientific Discovery},\n\n  year = {1995},\n\n  cicyt = {workshops},\n\n  key = {Other},\n\n  url = {spring95.ps.gz},\n\n  publisher = {AAAI},\n\n  address = {Stanford, CA (USA)},\n\n  month = {March},\n\n  pages = {60-65},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Integrating Planning and Learning: The \\sc prodigy Architecture.\n \n \n \n \n\n\n \n Veloso, M.; Carbonell, J.; Pérez, A.; Borrajo, D.; Fink, E.; and Blythe, J.\n\n\n \n\n\n\n Journal of Experimental and Theoretical AI, 7: 81-120. 1995.\n \n\n\n\n
\n\n\n\n \n \n $\"Integrating$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jetai,\n\n  author = {Manuela Veloso and Jaime Carbonell and Alicia Pérez\n\n\tand Daniel Borrajo and Eugene Fink and Jim Blythe},\n\n  title = {Integrating Planning and Learning: The {\\sc prodigy}\n\n\tArchitecture},\n\n  journal = {Journal of Experimental and Theoretical AI},\n\n  volume = {7},\n\n  pages = {81-120},\n\n  year = {1995},\n\n  cicyt = {revista},\n\n  jcr = {Q3, 1997: 0.27 (32/54)},\n\n  optjcr = {2004: 0.556 (54/78), 2005: 0.439 (66/79), 2006: 0.297 (77/85), 2007: 0.500 (72/93)},\n\n  key = {Planning-Learning},\n\n  url = {http://hdl.handle.net/10016/6770}\n\n}\n\n\n\n

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\n \n 1994\n \n \n (4)\n \n \n

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\n \n\n \n \n \n \n \n \n Learning Strategy Knowledge Incrementally.\n \n \n \n \n\n\n \n Veloso, M.; and Borrajo, D.\n\n\n \n\n\n\n In Proceedings of the Sixth IEEE International Conference on Tools with Artificial Intelligence, pages 484-490, New Orleans, LA, November 1994. IEEE Computer Society Press\n http://dx.doi.org/10.1109/TAI.1994.346453\n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ieee94,\n\n  author = {Manuela Veloso and Daniel Borrajo},\n\n  title = {Learning Strategy Knowledge Incrementally},\n\n  booktitle = {Proceedings of the Sixth IEEE International\n\n\tConference on Tools with Artificial Intelligence},\n\n  year = {1994},\n\n  month = {November},\n\n  address = {New Orleans, LA},\n\n  url = {http://hdl.handle.net/10016/6841},\n\n  cicyt = {congresos},\n\n  key = {Planning-Learning},\n\n  pages = {484-490},\n\n  publisher = {IEEE Computer Society Press},\n\n  jcr = {B},\n\n  note = {http://dx.doi.org/10.1109/TAI.1994.346453}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Incremental Learning of Quality-Oriented Control Knowledge for Planning.\n \n \n \n \n\n\n \n Borrajo, D.; and Veloso, M.\n\n\n \n\n\n\n In Working notes of the AAAI Fall Series Symposium 1994 on Planning and Learning, New Orleans, LO, November 1994. \n \n\n\n\n
\n\n\n\n \n \n $\"Incremental$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{fall94,\n\n  author = {Daniel Borrajo and Manuela Veloso},\n\n  title = {Incremental Learning of Quality-Oriented Control\n\n\tKnowledge for Planning},\n\n  booktitle = {Working notes of the AAAI Fall Series Symposium\n\n\t1994 on Planning and Learning},\n\n  cicyt = {workshops},\n\n  year = {1994},\n\n  month = {November},\n\n  address = {New Orleans, LO},\n\n  pages = {},\n\n  key = {Planning-Learning},\n\n  url = {fall94.ps.gz},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Multiple Target Concept Learning and Revision in Nonlinear Problem Solving.\n \n \n \n \n\n\n \n Borrajo, D.; and Veloso, M.\n\n\n \n\n\n\n In Working notes of the ECML/MLNet Workshop on Theory Revision and Restructuring, Sicily, Italy, 1994. \n \n\n\n\n
\n\n\n\n \n \n $\"Multiple$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{revision94,\n\n  author = {Daniel Borrajo and Manuela Veloso},\n\n  title = {Multiple Target Concept Learning and Revision\n\n\tin Nonlinear Problem Solving},\n\n  booktitle = {Working notes of the ECML/MLNet Workshop on Theory\n\n\tRevision and Restructuring},\n\n  cicyt = {workshops},\n\n  year = {1994},\n\n  month = {},\n\n  address = {Sicily, Italy},\n\n  pages = {},\n\n  key = {Planning-Learning},\n\n  url = {revision94.ps.gz},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Incremental Learning of Control Knowledge for Nonlinear Problem Solving.\n \n \n \n \n\n\n \n Borrajo, D.; and Veloso, M.\n\n\n \n\n\n\n In Machine Learning: ECML-94, of Lecture Notes in Artificial Intelligence, pages 64-82, Sicily, Italy, 1994. Springer-Verlag\n \n\n\n\n
\n\n\n\n \n \n $\"Incremental$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ecml94,\n\n  author = {Daniel Borrajo and Manuela Veloso},\n\n  title = {Incremental Learning of Control Knowledge for Nonlinear Problem Solving},\n\n  booktitle = {Machine Learning: ECML-94},\n\n  publisher = {Springer-Verlag},\n\n  series = {Lecture Notes in Artificial Intelligence},\n\n  cicyt = {congresos-buenos},\n\n  number = {LNAI 784},\n\n  year = {1994},\n\n  pages = {64-82},\n\n  month = {},\n\n  address = {Sicily, Italy},\n\n  key = {Planning-Learning},\n\n  url = {ecml94.ps.gz},\n\n  jcr = {A}\n\n}\n\n\n\n

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\n \n 1993\n \n \n (1)\n \n \n

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\n \n\n \n \n \n \n \n \n Bounded Explanation and Inductive Refinement for Acquiring Control Knowledge.\n \n \n \n \n\n\n \n Borrajo, D.; and Veloso, M.\n\n\n \n\n\n\n In Proceedings of the Third International Workshop on Knowledge Compilation and Speedup Learning, pages 21-27, Amherst, MA, June 1993. \n \n\n\n\n
\n\n\n\n \n \n $\"Bounded$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{ml93,\n\n  author = {Daniel Borrajo and Manuela Veloso},\n\n  title = {Bounded Explanation and Inductive Refinement \n\n\tfor Acquiring Control Knowledge},\n\n  booktitle = {Proceedings of the Third International\n\n\tWorkshop on Knowledge Compilation and Speedup Learning},\n\n  cicyt = {workshops},\n\n  year = {1993},\n\n  month = {June},\n\n  address = {Amherst, MA},\n\n  pages = {21-27},\n\n  key = {Planning-Learning},\n\n  url = {ml93.ps.gz},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n 1992\n \n \n (1)\n \n \n

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\n \n\n \n \n \n \n \n A Knowledge Compilation Model for Learning Heuristics.\n \n \n \n\n\n \n Borrajo, D.; Caraça-Valente, J. P.; and Pazos, J.\n\n\n \n\n\n\n In Proceedings of the ML92 Workshop on Knowledge Compilation and Speedup Learning, Aberdeen, Scotland, 1992. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{workshopml92,\n\n  author = {Daniel Borrajo and Juan P. Cara\\c{c}a-Valente\n\n\tand Juan Pazos},\n\n  title = {A Knowledge Compilation Model for Learning Heuristics},\n\n  cicyt = {workshops},\n\n  booktitle = {Proceedings of the ML92 Workshop on Knowledge Compilation\n\n\t\t  and Speedup Learning},\n\n  year = {1992},\n\n  key = {Planning-Learning},\n\n  address = {Aberdeen, Scotland},\n\n  jcr = {}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n Integrating the users in the design of a robot for making Comprehensive Geriatric Assessments (CGA) to elderly people in care centers.\n \n \n \n\n\n \n Lan, K.; Ting, H.; Voilmy, D.; Iglesias, A.; Pulido, J. C.; García, J.; Romero-Garcés, A.; Bandera, J. P.; Marfil, R.; and Dueñas, A.\n\n\n \n\n\n\n . .\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{Lan,\nabstract = {— Comprehensive Geriatric Assessment (CGA) is a multidimensional and multidisciplinary diagnostic instrument that helps provide personalized care to the elderly, by evaluating their physical and mental state. In a social and economic context of growing ageing populations, medical experts can save time and effort if provided with interactive tools to efficiently assist them in doing CGAs, managing standardized tests or data collection. Recent research proposes the use of social robots as the central part of these tools. These robots must be able to unfold all functionalities that questionnaires or motion-based tests require, including natural language, face tracking and monitoring, human motion capture and so on. But another issue is the robot's acceptability and trust by the end-users, both patients (elderly people) and clinicians: the robot needs to be able to engage with the patients during the interaction sessions, and must be perceived as a useful and efficient tool by the clinicians. This paper presents the acquisition of new user requirements for CLARC, through participatory and user-centered design approach, to inform the improvement of both interface and interaction. Thirty eight persons (elderly people, caregivers and health professionals) were involved in the design process of CLARC, based on user-centered methods and techniques of Human-Computer Interaction discipline.},\nauthor = {Lan, Karine and Ting, Hing and Voilmy, Dimitri and Iglesias, Ana and Pulido, Jos{\\'{e}} Carlos and Garc{\\'{i}}a, Javier and Romero-Garc{\\'{e}}s, Adri{\\'{a}}n and Bandera, Juan Pedro and Marfil, Rebeca and Due{\\~{n}}as, Alvaro},\nfile = {:home/fernando/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Lan et al. - Unknown - Integrating the users in the design of a robot for making Comprehensive Geriatric Assessments (CGA) to elderly pe.pdf:pdf},\ntitle = {{Integrating the users in the design of a robot for making Comprehensive Geriatric Assessments (CGA) to elderly people in care centers}}\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n On-line modelling and planning for urban traffic control.\n \n \n \n \n\n\n \n Pozanco, A.; Fernández, S.; and Borrajo, D.\n\n\n \n\n\n\n Expert Systems, n/a(n/a): e12693. .\n \n\n\n\n
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@article{https://doi.org/10.1111/exsy.12693,\nauthor = {Pozanco, Alberto and Fernández, Susana and Borrajo, Daniel},\ntitle = {On-line modelling and planning for urban traffic control},\njournal = {Expert Systems},\nvolume = {n/a},\nnumber = {n/a},\npages = {e12693},\nkeywords = {automated planning, distributed planning, model learning, urban traffic control},\ndoi = {https://doi.org/10.1111/exsy.12693},\nurl = {https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.12693},\neprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.12693},\nabstract = {Abstract Urban Traffic Control is a key problem for most big cities. Current approaches to handle the city traffic rely on controlling traffic lights. The systems in operation range from static control of traffic light phases to adaptive systems based on numeric models and traffic sensors. Recently, some planning-based approaches have also been proposed. These approaches work at a higher level of abstraction, but have been found to work well if complemented by low-level systems. We have identified two main difficulties for the wide use of planning techniques in this domain: generating the control models is a difficult task; and some algorithms scale poorly. In this paper we present Automated Planning for Traffic Control (APTC), a control system based on Automated Planning, that successfully overcomes these two problems. It combines techniques that continuously: learn an accurate planning model; and also divide the city for distributed reasoning in order to scale to large city networks. Experimental results show that APTC outperforms static approaches as well as other planning-based systems. We also show that the combination of both approaches improves compared with using only one of them.}\n}\n\n

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\n \n\n \n \n \n \n \n Business Simulation in Business Education.\n \n \n \n\n\n \n Borrajo, F.; Bueno, Y.; Fernández, F.; García, J.; de Pablo, I.; Sagredo, I.; and Santos, B.\n\n\n \n\n\n\n Distance Education, pages 101-126. Nova Science Publishers, In Press.\n \n\n\n\n
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@inbook{simba-nova,\n\n  author = {Fernando Borrajo and Yolanda Bueno and Fernando Fernández and Javier García and Isidro de Pablo and Ismael Sagredo and Begoña Santos},\n\n  title = {Distance Education},\n\n  chapter = {Business Simulation in Business Education},\n\n  publisher = {Nova Science Publishers},\n\n  key = {Other},\n\n  year = {In Press},\n\n  optvolume = {},\n\n  pages = {101-126}\n\n}\n\n\n\n

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\n \n\n \n \n \n \n \n On the importance of breaking ties in the relaxed plan heuristic.\n \n \n \n\n\n \n De la Rosa, T.; and Fuentetaja, R.\n\n\n \n\n\n\n Journal of Experimental and Theoretical Artificial Intelligence. In Press.\n \n\n\n\n
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@article{hdiff_JETAI,\n\n  author = {Tomás {De la Rosa} and Raquel Fuentetaja},\n\n  title = {On the importance of breaking ties in the relaxed plan heuristic},\n\n  key = {Planning-Learning},\n\n  journal = {Journal of Experimental and Theoretical Artificial Intelligence},\n\n  year = {In Press},\n\n  cicyt = {revista}\n\n}\n\n\n\n

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