Skip to Main content Skip to Navigation
Journal articles

A big-stepped probability approach for discovering default rules

Salem Benferhat 1 Didier Dubois 1 Sylvain Lagrue 1 Henri Prade 1
1 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
IRIT - Institut de recherche en informatique de Toulouse
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.
Keywords : knowledge discovery default rules non-monotonic reasoning big stepped probabilities possibility theory
Document type :
Journal articles
Complete list of metadata
https://hal-univ-artois.archives-ouvertes.fr/hal-03299557
Contributor : Fabien Delorme Connect in order to contact the contributor
Submitted on : Monday, July 26, 2021 - 3:24:35 PM
Last modification on : Tuesday, October 19, 2021 - 2:23:19 PM

Identifiers

Collections

UNIV-ARTOIS | UNIV-TLSE3 | UT1-CAPITOLE | UNIV-TLSE2 | CNRS | IRIT | IRIT-ADRIA | IRIT-IA

Citation

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, World Scientific Publishing, 2003, 11 (sppl. 01), pp.1-14. ⟨10.1142/S0218488503002235⟩. ⟨hal-03299557⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Les métriques sont temporairement indisponibles