{"type":"ScholarlyArticle","title":"A Dynamic Approach for MPE and Weighted MAX-SAT","authors":[{"name":"Tian Sang","slug":"tian-sang","given":"Tian","family":"Sang","affiliation":""},{"name":"Paul Beame","slug":"paul-beame","given":"Paul","family":"Beame","affiliation":""},{"name":"Henry A. Kautz","slug":"henry-a-kautz","given":"Henry A.","family":"Kautz","affiliation":""}],"abstract":"The problem of Most Probable Explanation (MPE) arises in the scenario of probabilistic inference: finding an assignment to all variables that has the maximum likelihood given some evidence. We consider the more general CNF-based MPE problem, where each literal in a CNF-formula is associated with a weight. We describe reductions between MPE and weighted MAX-SAT, and show that both can be solved by a variant of weighted model counting. The MPE-SAT algorithm is quite competitive with the state-of-the-art MAX-SAT, WCSP, and MPE solvers on a variety of problems.","doi":null,"url":"https://ijcai.org/proceedings/2007/26","pdf":"https://ijcai.org/proceedings/2007/0026.pdf","markdown":"https://ijcai.org/proceedings/2007/26.md","bibtex":"https://ijcai.org/proceedings/2007/bibtex/26","volume":{"slug":"2007","title":"Proceedings of the Twentieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2007","url":"https://ijcai.org/proceedings/2007/","year":2007,"location":"Hyderabad, India","dates":"","editors":"Ramon López de Mántaras","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":26,"pages":{"first":173,"last":178},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}