{"type":"ScholarlyArticle","title":"Learning Possibilistic Logic Theories from Default Rules","authors":[{"name":"Ondrej Kuzelka","slug":"ondrej-kuzelka","given":"Ondrej","family":"Kuzelka","affiliation":""},{"name":"Jesse Davis","slug":"jesse-davis","given":"Jesse","family":"Davis","affiliation":""},{"name":"Steven Schockaert","slug":"steven-schockaert","given":"Steven","family":"Schockaert","affiliation":""}],"abstract":"We introduce a setting for learning possibilistic logic theories from defaults of the form if alpha then typically beta. We first analyse this problem from the point of view of machine learning theory, determining the VC dimension of possibilistic stratifications as well as the complexity of the associated learning problems, after which we present a heuristic learning algorithm that can easily scale to thousands of defaults. An important property of our approach is that it is inherently able to handle noisy and conflicting sets of defaults. Among others, this allows us to learn possibilistic logic theories from crowdsourced data and to approximate propositional Markov logic networks using heuristic MAP solvers. We present experimental results that demonstrate the effectiveness of this approach.","doi":null,"url":"https://ijcai.org/proceedings/2016/169","pdf":"https://ijcai.org/proceedings/2016/0169.pdf","markdown":"https://ijcai.org/proceedings/2016/169.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/169","volume":{"slug":"2016","title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2016","url":"https://ijcai.org/proceedings/2016/","year":2016,"location":"New York, NY, USA","dates":"9–15 July 2016","editors":"Subbarao Kambhampati","isbn":"978-1-57735-770-4; 978-1-57735-771-1","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":169,"pages":{"first":1167,"last":1172},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}