Compatible-based Conditioning in Interval-based Possibilistic Logic

Salem Benferhat, Amelie Levray, Karim Tabia, Vladik Kreinovich

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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 intervalbased 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.
Original languageEnglish
Title of host publicationProceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI’15), 2015.
Place of PublicationBuenos Aires, Argentina
Number of pages7
Publication statusPublished - 2015
Event24th International Joint Conference on Artificial Intelligence 2015 - Buenos Aires, Argentina
Duration: 25 Jul 201531 Jul 2015


Conference24th International Joint Conference on Artificial Intelligence 2015
Abbreviated titleIJCAI 2015
CityBuenos Aires
Internet address


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