{"type":"ScholarlyArticle","title":"Learning Generalized Policies for Fully Observable Non-Deterministic Planning Domains","authors":[{"name":"Till Hofmann","slug":"till-hofmann","given":"Till","family":"Hofmann","affiliation":"RWTH Aachen University"},{"name":"Hector Geffner","slug":"hector-geffner","given":"Hector","family":"Geffner","affiliation":"RWTH Aachen University"}],"abstract":"General policies represent reactive strategies for solving large families of planning problems like the infinite collection of solvable instances from a given domain. Methods for learning such policies from a collection of small training instances have been developed successfully for classical domains. In this work, we extend the formulations and the resulting combinatorial methods for learning general policies over fully observable, non-deterministic (FOND) domains. We also evaluate the resulting approach experimentally over a number of benchmark domains in FOND planning, present the general policies that result in some of these domains, and prove their correctness. The method for learning general policies for FOND planning can actually be seen as an alternative planning FOND planning method that searches for solutions not in the given state space but in an abstract state space defined by features that must be learned as well.","doi":"10.24963/ijcai.2024/744","url":"https://ijcai.org/proceedings/2024/744","pdf":"https://ijcai.org/proceedings/2024/0744.pdf","markdown":"https://ijcai.org/proceedings/2024/744.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/744","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Planning and Scheduling","track":"Main Track","number":744,"pages":{"first":6733,"last":6742},"keywords":["Planning and Scheduling: PS: Learning in planning and scheduling","Planning and Scheduling: PS: Planning under uncertainty"],"videos":[],"references":[{"position":1,"raw":"[Baader et al., 2008] Frank Baader, Ian Horrocks, and Ulrike Sat- tler. 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