{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/compact-policies-for-fully-observable-non","title":"Compact Policies for Fully-Observable Non-Deterministic Planning as SAT","arxiv_id":"1806.09455","date":"2018-06-25","proceeding":null,"authors":["Tomas Geffner","Hector Geffner"],"abstract":"Fully observable non-deterministic (FOND) planning is becoming increasingly\nimportant as an approach for computing proper policies in probabilistic\nplanning, extended temporal plans in LTL planning, and general plans in\ngeneralized planning. In this work, we introduce a SAT encoding for FOND\nplanning that is compact and can produce compact strong cyclic policies. Simple\nvariations of the encodings are also introduced for strong planning and for\nwhat we call, dual FOND planning, where some non-deterministic actions are\nassumed to be fair (e.g., probabilistic) and others unfair (e.g., adversarial).\nThe resulting FOND planners are compared empirically with existing planners\nover existing and new benchmarks. The notion of \"probabilistic interesting\nproblems\" is also revisited to yield a more comprehensive picture of the\nstrengths and limitations of current FOND planners and the proposed SAT\napproach.","url_abs":"http://arxiv.org/abs/1806.09455v1","url_pdf":"http://arxiv.org/pdf/1806.09455v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"compact-policies-for-fully-observable-non","repo_url":"https://github.com/tomsons22/FOND-SAT","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}