{"type":"ScholarlyArticle","title":"On Consensus Extraction","authors":[{"name":"Éric Grégoire","slug":"eric-gregoire","given":"Éric","family":"Grégoire","affiliation":""},{"name":"Sébastien Konieczny","slug":"sebastien-konieczny","given":"Sébastien","family":"Konieczny","affiliation":""},{"name":"Jean-Marie Lagniez","slug":"jean-marie-lagniez","given":"Jean-Marie","family":"Lagniez","affiliation":""}],"abstract":"Computing a consensus is a key task in various AI areas, ranging from belief fusion, social choice,negotiation, etc. In this work, we define consensus operators as functions that deliver parts of the set-theoretical union of the information sources (inpropositional logic) to be reconciled, such that no source is logically contradicted. We also investigate different notions of maximality related to these consensuses. From a computational point of view, we propose a generic problem transformation that leads to a method that proves experimentally efficient very often, even for large conflicting sources to be reconciled.","doi":null,"url":"https://ijcai.org/proceedings/2016/159","pdf":"https://ijcai.org/proceedings/2016/0159.pdf","markdown":"https://ijcai.org/proceedings/2016/159.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/159","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":159,"pages":{"first":1095,"last":1100},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}