Proceedings

Description Logics and Fuzzy Probability

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 1075-1080.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-184

Abstract

Uncertainty and vagueness are pervasive phenomena in real-life knowledge. They are supported in extended description logics that adapt classical description logics to deal with numerical probabilities or fuzzy truth degrees. While the two concepts are distinguished for good reasons, they combine in the notion of probably, which is ultimately a fuzzy qualification of probabilities. Here, we develop existing propositional logics of fuzzy probability into a full-blown description logic, and we show decidability of several variants of this logic under Lukasiewicz semantics. We obtain these results in a novel generic framework of fuzzy coalgebraic logic; this enables us to extend our results to logics that combine crisp ingredients including standard crisp roles and crisp numerical probabilities with fuzzy roles and fuzzy probabilities.

Lutz Schröder, and Dirk Pattinson. 2011. Description Logics and Fuzzy Probability. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 1075–1080. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-184
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