A big-stepped probability approach for discovering default rules

Authors:
Salem Benferhat;Didier Dubois;Sylvain Lagrue;Henri Prade
Affiliations:
CRIL, Université d'Artois, Rue de l'Université, SP 16, 62307 Lens Cedex;IRIT, Univerisité Paul Sabatier, 118, route de Narbonne, 31062 Toulouse Cedex 4, France;SOMEI/PRAXITEC, 115, rue St. Jacques, 13006 Marseille, France;IRIT, Univerisité Paul Sabatier, 118, route de Narbonne, 31062 Toulouse Cedex 4, France
Venue:
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems - Intelligent information systems
Year:
2003

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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.