{"type":"ScholarlyArticle","title":"Variable and Value Ordering for MPE Search","authors":[{"name":"Sajjad Ahmed Siddiqi","slug":"sajjad-ahmed-siddiqi","given":"Sajjad Ahmed","family":"Siddiqi","affiliation":""},{"name":"Jinbo Huang","slug":"jinbo-huang","given":"Jinbo","family":"Huang","affiliation":""}],"abstract":"In Bayesian networks, a most probable explanation (MPE) is a most likely instantiation of all network variables given a piece of evidence. Solving (the decision version of) an MPE query is NP-hard. Recent work proposed a branch-and-bound search algorithm that finds exact solutions to MPE queries, where bounds are computed on a relaxed network obtained by a technique known as node splitting. In this work we study the impact of variable and value ordering on such a search algorithm. We study several heuristics based on the entropies of variables and on the notion of nogoods, and propose a new meta-heuristic that combines their strengths. Experiments indicate that search efficiency is significantly improved, allowing many hard problems to be solved for the first time.Sajjad Ahmed Siddiqi, Jinbo Huang","doi":null,"url":"https://ijcai.org/proceedings/2009/324","pdf":"https://ijcai.org/proceedings/2009/0324.pdf","markdown":"https://ijcai.org/proceedings/2009/324.md","bibtex":"https://ijcai.org/proceedings/2009/bibtex/324","volume":{"slug":"2009","title":"Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2009","url":"https://ijcai.org/proceedings/2009/","year":2009,"location":"Pasadena, California, USA","dates":"","editors":"Hiroaki Kitano","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":324,"pages":{"first":1964,"last":1968},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}