var bibbase_data = {"data":"<img src=\"//bibbase.org/img/ajax-loader.gif\" id=\"spinner\"\n  style=\"display: none;\" alt=\"Loading..\" />\n\n<div id=\"bibbase\">\n\n  <script type=\"text/javascript\">\n    var bibbase = {\n      params: {\"bib\":\"https://bercher.net/bibtex/04-Yousefi/all.bib\",\"theme\":\"default\",\"fullnames\":\"1\",\"jsonp\":\"1\",\"hidemenu\":\"1\",\"host\":\"bibbase.org\"},\n      data: [{\"bibtype\":\"inproceedings\",\"type\":\"inproceedings\",\"author\":[{\"firstnames\":[\"Mohammad\"],\"propositions\":[],\"lastnames\":[\"Yousefi\"],\"suffixes\":[]},{\"firstnames\":[\"Pascal\"],\"propositions\":[],\"lastnames\":[\"Bercher\"],\"suffixes\":[]}],\"booktitle\":\"Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024)\",\"title\":\"Laying the Foundations for Solving FOND HTN Problems: Grounding, Search, Heuristics (and Benchmark Problems)\",\"year\":\"2024\",\"xpages\":\"\",\"xdoi\":\"\",\"publisher\":\"IJCAI\",\"abstract\":\"Building upon recent advancements in formalising Fully Observable Non-Deterministic (FOND) Hierarchical Task Network (HTN) planning, we present the first approach to find strong solutions for HTN problems with uncertainty in action outcomes. 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This allows the utilisation of existing grounders and heuristics from the deterministic HTN planning literature.\",\"xurl_paper\":\"\",\"xurl_slides\":\"\",\"xurl_video_of_presentation\":\"\",\"bibtex\":\"@InProceedings{Yousefi2024FONDFoundations,\\n  author     = {Mohammad Yousefi and Pascal Bercher},\\n  booktitle  = {Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024)},\\n  title      = {Laying the Foundations for Solving {FOND} {HTN} Problems: Grounding, Search, Heuristics (and Benchmark Problems)},\\n  year       = {2024},\\n Xpages      = {},\\n Xdoi        = {},\\n  publisher  = {IJCAI},\\n  abstract   = {Building upon recent advancements in formalising Fully Observable Non-Deterministic (FOND) Hierarchical Task Network (HTN) planning, we present the first approach to find strong solutions for HTN problems with uncertainty in action outcomes. 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More specifically, the extension can identify potential flaws in a domain and propose respective corrections by taking as input a set of counter-example plans, which are known to be valid but actually contradict the domain. Those input plans shall be provided by the user. The flaws are then identified and corrected by making changes to the domain so as to turn those plans into solutions, i.e., the changes are regarded as potential corrections to the domain. 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IJCAI\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yousefi-bercher-layingthefoundationsforsolvingfondhtnproblemsgroundingsearchheuristicsandbenchmarkproblems-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yousefi-bercher-layingthefoundationsforsolvingfondhtnproblemsgroundingsearchheuristicsandbenchmarkproblems-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@InProceedings{Yousefi2024FONDFoundations,\n  author     = {Mohammad Yousefi and Pascal Bercher},\n  booktitle  = {Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024)},\n  title      = {Laying the Foundations for Solving {FOND} {HTN} Problems: Grounding, Search, Heuristics (and Benchmark Problems)},\n  year       = {2024},\n Xpages      = {},\n Xdoi        = {},\n  publisher  = {IJCAI},\n  abstract   = {Building upon recent advancements in formalising Fully Observable Non-Deterministic (FOND) Hierarchical Task Network (HTN) planning, we present the first approach to find strong solutions for HTN problems with uncertainty in action outcomes. We present a search algorithm, along with a compilation that relaxes a FOND HTN problem to a deterministic one. This allows the utilisation of existing grounders and heuristics from the deterministic HTN planning literature.},\n Xurl_Paper  = {},\n Xurl_Slides = {},\n Xurl_video_of_presentation = {}\n}\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Building upon recent advancements in formalising Fully Observable Non-Deterministic (FOND) Hierarchical Task Network (HTN) planning, we present the first approach to find strong solutions for HTN problems with uncertainty in action outcomes. We present a search algorithm, along with a compilation that relaxes a FOND HTN problem to a deterministic one. This allows the utilisation of existing grounders and heuristics from the deterministic HTN planning literature.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lin-yousefi-bercher-avisualstudiocodeextensionforautomaticallyrepairingplanningdomains-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A Visual Studio Code Extension for Automatically Repairing Planning Domains.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n   Songtuan Lin;  Mohammad Yousefi;  and  Pascal Bercher.\n</span>\n\n  \n\n</span>\n\n  In <i>ICAPS 2024 Demonstrations</i>,  2024. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lin-yousefi-bercher-avisualstudiocodeextensionforautomaticallyrepairingplanningdomains-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lin-yousefi-bercher-avisualstudiocodeextensionforautomaticallyrepairingplanningdomains-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@InProceedings{Lin2024VSPlugin,\n  author    = {Songtuan Lin and Mohammad Yousefi and Pascal Bercher},\n  booktitle = {ICAPS 2024 Demonstrations},\n  title     = {A Visual Studio Code Extension for Automatically Repairing Planning Domains},\n  year      = {2024},\n  abstract  = {We demonstrate a Visual Studio Code extension which aims at providing modeling assistance for modeling planning domains in PDDL. More specifically, the extension can identify potential flaws in a domain and propose respective corrections by taking as input a set of counter-example plans, which are known to be valid but actually contradict the domain. Those input plans shall be provided by the user. The flaws are then identified and corrected by making changes to the domain so as to turn those plans into solutions, i.e., the changes are regarded as potential corrections to the domain. Currently, the extension only supports corrections that add predicates to or remove predicates from actions&#x27; preconditions and effects.}\n}\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We demonstrate a Visual Studio Code extension which aims at providing modeling assistance for modeling planning domains in PDDL. More specifically, the extension can identify potential flaws in a domain and propose respective corrections by taking as input a set of counter-example plans, which are known to be valid but actually contradict the domain. Those input plans shall be provided by the user. The flaws are then identified and corrected by making changes to the domain so as to turn those plans into solutions, i.e., the changes are regarded as potential corrections to the domain. Currently, the extension only supports corrections that add predicates to or remove predicates from actions' preconditions and effects.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n\n\n\n  </div>\n\n\n  <!-- Modal -->\n\n  <!-- <iframe id=\"bibbase_network_frame\" -->\n  <!--         src=\"//bibbase.org/network/control\" -->\n  <!--         style=\"display: none;\"> -->\n  <!-- </iframe> -->\n\n</div>\n"}; document.write(bibbase_data.data);