{"type":"ScholarlyArticle","title":"Real-Time Search in Non-Deterministic Domains","authors":[{"name":"Sven Koenig","slug":"sven-koenig","given":"Sven","family":"Koenig","affiliation":""},{"name":"Reid G. Simmons","slug":"reid-g-simmons","given":"Reid G.","family":"Simmons","affiliation":""}],"abstract":"Many search domains are non-deterministic. Although real-time search methods have traditionally been studied in deterministic domains, they are well suited for searching nondeterministic domains since they do not have to plan for every contingency - they can react to the actual outcomes of actions. In this paper, we introduce the min-max LRTA * algorithm, a simple extension of Korf's Learning Real- Time A* algorithm (LRTA *) to non-deterministic domains. We describe which non-deterministic domains min-max LRTA * can solve, and analyze its performance for these domains. We also give tight bounds on its worst-case performance and show how this performance depends on properties of both the domains and the heuristic functions used to encode prior information about the domains.","doi":null,"url":"https://ijcai.org/proceedings/1995/214","pdf":"https://ijcai.org/proceedings/1995/0214.pdf","markdown":"https://ijcai.org/proceedings/1995/214.md","bibtex":"https://ijcai.org/proceedings/1995/bibtex/214","volume":{"slug":"1995","title":"Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1995","url":"https://ijcai.org/proceedings/1995/","year":1995,"location":"Montréal, Québec, Canada","dates":"","editors":"Chris S. Mellish","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Planning","track":"Planning","number":214,"pages":{"first":1660,"last":1668},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}