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 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 language | English |
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Title of host publication | Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI’15), 2015. |
Place of Publication | Buenos Aires, Argentina |
Pages | 2777-2783 |
Number of pages | 7 |
Publication status | Published - 2015 |
Event | 24th International Joint Conference on Artificial Intelligence 2015 - Buenos Aires, Argentina Duration: 25 Jul 2015 → 31 Jul 2015 https://ijcai-15.org/ |
Conference
Conference | 24th International Joint Conference on Artificial Intelligence 2015 |
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Abbreviated title | IJCAI 2015 |
Country/Territory | Argentina |
City | Buenos Aires |
Period | 25/07/15 → 31/07/15 |
Internet address |