{"type":"ScholarlyArticle","title":"Compatible-Based Conditioning in Interval-Based Possibilistic Logic","authors":[{"name":"Salem Benferhat","slug":"salem-benferhat","given":"Salem","family":"Benferhat","affiliation":""},{"name":"Amélie Levray","slug":"amelie-levray","given":"Amélie","family":"Levray","affiliation":""},{"name":"Karim Tabia","slug":"karim-tabia","given":"Karim","family":"Tabia","affiliation":""},{"name":"Vladik Kreinovich","slug":"vladik-kreinovich","given":"Vladik","family":"Kreinovich","affiliation":""}],"abstract":"Interval-based possibilistic logic is a flexible setting extending standard possibilistic logic such that each logical expression is associated with a sub-interval of [0,1]. This paper focuses on the fundamental issue of conditioning in the interval-based possibilistic setting. The first part of the paper first proposes a set of natural properties that an interval-based conditioning operator should satisfy. We then give a natural and safe definition for conditioning an interval-based possibility distribution. This definition is based on applying standard min-based or product-based conditioning on the set of all associated compatible possibility distributions. We analyze the obtained posterior distributions and provide a precise characterization of lower and upper endpoints of the intervals associated with interpretations. The second part of the paper provides an equivalent syntactic computation of interval-based conditioning when interval-based distributions are compactly encoded by means of interval-based possibilistic knowledge bases. We show that interval-based conditioning is achieved without extra computational cost comparing to conditioning standard possibilistic knowledge bases.","doi":null,"url":"https://ijcai.org/proceedings/2015/393","pdf":"https://ijcai.org/proceedings/2015/0393.pdf","markdown":"https://ijcai.org/proceedings/2015/393.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/393","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Special Track on Knowledge Representation and Reasoning","track":"Special Track on Knowledge Representation and Reasoning","number":393,"pages":{"first":2777,"last":2782},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}