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\n  \n 2024\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Modeling Assistance for Hierarchical Planning: An Approach for Correcting Hierarchical Domains with Missing Actions.\n \n \n \n\n\n \n Songtuan Lin; Daniel Höller; and Pascal Bercher.\n\n\n \n\n\n\n In Proceedings of the 17th International Symposium on Combinatorial Search (SoCS 2024), 2024. AAAI 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 abstract \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{Lin2024HTNRepair,\n  author    = {Songtuan Lin and Daniel Höller and Pascal Bercher},\n  booktitle = {Proceedings of the 17th International Symposium on Combinatorial Search (SoCS 2024)},\n  title     = {Modeling Assistance for Hierarchical Planning: An Approach for Correcting Hierarchical Domains with Missing Actions},\n  year      = {2024},\n  publisher = {AAAI Press},\n  abstract  = {The complexity of modeling planning domains is a major obstacle for making automated planning techniques more accessible, raising the demand of tools for providing modeling assistance. In particular, tools that can automatically correct errors in a planning domain are of great importance. Previous works have devoted efforts to developing such approaches for correcting classical  (non-hierarchical) domains. However, no approaches exist for hierarchical planning, which is what we offer here. More specifically, our approach takes as input a flawed hierarchical domain together with a plan known to be a solution but actually contradicting the domain (due to errors in the domain) and outputs corrections to the domain that add \\emph{missing} actions to the domain and make the plan a solution. The approach achieves this by compiling the problem of finding corrections as another hierarchical planning problem.},\n}\n\n
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\n The complexity of modeling planning domains is a major obstacle for making automated planning techniques more accessible, raising the demand of tools for providing modeling assistance. In particular, tools that can automatically correct errors in a planning domain are of great importance. Previous works have devoted efforts to developing such approaches for correcting classical (non-hierarchical) domains. However, no approaches exist for hierarchical planning, which is what we offer here. More specifically, our approach takes as input a flawed hierarchical domain together with a plan known to be a solution but actually contradicting the domain (due to errors in the domain) and outputs corrections to the domain that add \\emphmissing actions to the domain and make the plan a solution. The approach achieves this by compiling the problem of finding corrections as another hierarchical planning problem.\n
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\n  \n 2023\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n On Semantics of Hierarchical Planning Domain Models with Decomposition Constraints and Empty Methods.\n \n \n \n \n\n\n \n Simona Ondrčková; and Roman Barták.\n\n\n \n\n\n\n In Proceedings of the 35th International Conference on Tools with Artificial Intelligence (ICTAI 2023), pages 349–353, 2023. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"OnPaper\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
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@InProceedings{Ondrckova2023HTNFormalism,\n  author    = {Simona Ondrčková and Roman Barták},\n  booktitle = {Proceedings of the 35th International Conference on Tools with Artificial Intelligence (ICTAI 2023)},\n  title     = {On Semantics of Hierarchical Planning Domain Models with Decomposition Constraints and Empty Methods},\n  year      = {2023},\n  pages     = {349--353},\n  publisher = {IEEE},\n  abstract  = {There are multiple formalisms describing hierarchical planning domain models, however many of them do not show semantics of some features such as empty decomposition methods and extensive constraints. In this short paper we describe the semantics of a hierarchical domain model with these extensive constraints and show how empty decomposition methods would work within it. We also compare this model with other models and present some transformations of model properties.},\n  doi       = {10.1109/ICTAI59109.2023.00057},\n  url       = {https://www.computer.org/csdl/proceedings-article/ictai/2023/427300a349/1T3dlwU23nO},\n}
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\n There are multiple formalisms describing hierarchical planning domain models, however many of them do not show semantics of some features such as empty decomposition methods and extensive constraints. In this short paper we describe the semantics of a hierarchical domain model with these extensive constraints and show how empty decomposition methods would work within it. We also compare this model with other models and present some transformations of model properties.\n
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