Proceedings

Compatible-Based Conditioning in Interval-Based Possibilistic Logic

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Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Special Track on Knowledge Representation and Reasoning. Pages 2777-2782.

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.

Salem Benferhat, Amélie Levray, Karim Tabia, and Vladik Kreinovich. 2015. Compatible-Based Conditioning in Interval-Based Possibilistic Logic. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 2777–2782. https://ijcai.org/proceedings/2015/393
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