{"type":"ScholarlyArticle","title":"Why AC-3 is Almost Always Better than AC4 for Establishing Arc Consistency in CSPs","authors":[{"name":"Richard J. Wallace","slug":"richard-j-wallace","given":"Richard J.","family":"Wallace","affiliation":""}],"abstract":"On the basis of its optimal asymptotic time complexity, AC-4 is often considered the best algorithm for establishing arc consistency in constraint satisfaction problems (CSPs). In the present work, AC3 was found to be much more efficient th~m AC-4, for CSPs with a variety of features. (Variable pairs were in lexical order, ~md in AC-3 they were added to the end of the list of pairs.) This is supported by arguments for the superiority of AC-3 over most of the nmge of constraint satisfiabilities ~md for the unlikelihood of conditions leading to worst-case perfonmmce. The efficiency of AC-4 is affected by the order of variable testing in Phase 1 ('setting up' phase); perform~mce in this phase can thus be enhanced, and this establishes initial conditions for Phase 2 that improve its performance. But, since AC-3 is improved by the smne orderings, it still outperforms AC-4 in most cases.","doi":null,"url":"https://ijcai.org/proceedings/1993/34","pdf":"https://ijcai.org/proceedings/1993/0034.pdf","markdown":"https://ijcai.org/proceedings/1993/34.md","bibtex":"https://ijcai.org/proceedings/1993/bibtex/34","volume":{"slug":"1993","title":"Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1993","url":"https://ijcai.org/proceedings/1993/","year":1993,"location":"Chambéry, France","dates":"","editors":"Ruzena Bajcsy","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Constraint Satisfaction Problems","track":"Constraint Satisfaction Problems","number":34,"pages":{"first":239,"last":246},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}