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A big-stepped probability approach for discovering default rules

Abstract : This paper deals with the extraction of default rules from a database of examples. The proposed approach is based on a special kind of probability distributions, called "big-stepped probabilities", which are known to provide a semantics for non-monotonic reasoning. The rules which are learnt are genuine default rules, which could be used (under some conditions) in a non-monotonic reasoning system and can be encoded in possibilistic logic.
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Contributor : Fabien DELORME Connect in order to contact the contributor
Submitted on : Monday, July 26, 2021 - 3:24:35 PM
Last modification on : Monday, July 4, 2022 - 10:03:36 AM



Salem Benferhat, Didier Dubois, Sylvain Lagrue, Henri Prade. A big-stepped probability approach for discovering default rules. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2003, 11 (sppl. 01), pp.1-14. ⟨10.1142/S0218488503002235⟩. ⟨hal-03299557⟩



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