{"type":"ScholarlyArticle","title":"Analyzing Tie-Breaking Strategies for the A* Algorithm","authors":[{"name":"Augusto B. Corrêa","slug":"augusto-b-correa","given":"Augusto B.","family":"Corrêa","affiliation":"University of Basel , Switzerland"},{"name":"André G. Pereira","slug":"andre-g-pereira","given":"André G.","family":"Pereira","affiliation":"Federal University of Rio Grande do Sul , Brazil"},{"name":"Marcus Ritt","slug":"marcus-ritt","given":"Marcus","family":"Ritt","affiliation":"Federal University of Rio Grande do Sul , Brazil"}],"abstract":"For a given state space and admissible heuristic function h there is always a tie-breaking strategy for which A* expands the minimum number of states [Dechter and Pearl, 1985]. We say that these strategies have optimal expansion. Although such a strategy always exists it may depend on the instance, and we currently do not know a tie-breaker that always guarantees optimal expansion. In this paper, we study tie-breaking strategies for A*. We analyze common strategies from the literature and prove that they do not have optimal expansion. We propose a novel tie-breaking strategy using cost adaptation that has always optimal expansion. We experimentally analyze the performance of A* using several tie-breaking strategies on domains from the IPC and zero-cost domains. Our best strategy solves significantly more instances than the standard method in the literature and more than the previous state-of-the-art strategy. Our analysis improves the understanding of how to develop effective tie-breaking strategies and our results also improve the state-of-the-art of tie-breaking strategies for A*.","doi":"10.24963/ijcai.2018/655","url":"https://ijcai.org/proceedings/2018/655","pdf":"https://ijcai.org/proceedings/2018/0655.pdf","markdown":"https://ijcai.org/proceedings/2018/655.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/655","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Planning and Scheduling","track":"Main track","number":655,"pages":{"first":4715,"last":4721},"keywords":["Planning and Scheduling: Theoretical Foundations of Planning","Planning and Scheduling: Search in Planning and Scheduling","Heuristic Search and Game Playing: Heuristic Search"],"videos":[],"references":[{"position":1,"raw":"[Asai and Fukunaga, 2016] Masataro Asai and Alex S Fuku- naga. 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