A local approach to reasoning under inconsistency in stratified knowledge bases

Salem Benferhat (1) , Didier Dubois (1) , Henri Prade (1)

1 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage

This paper investigates an approach for reasoning under inconsistency in a "local" way, in prioritized knowledge bases. In such bases, the higher the layer, the more certain, the more reliable are the formulas stored in this layer. The proposed approach is based on the notion of (consistent) argument whose strength depends on the layer of the least certain formulas involved in the argument. Each formula in the base is also associated with a "level of paraconsistency" which reflect to what extent there exists arguments that support both a formula and its negation. Three consequence relations are presented and compared. Two of them aim at maximizing the certainty degree and/or at minimizing the level of paraconsistency of the conclusion. The third one produces consequences that are safely supported in the sense that there exists an undefeated argument for them (whose certainty is greater than its paraconsistency).

Keywords: certain formula; undefeated argument; certainty degree; local way; consequence relation; introduction inconsistency; knowledge base; plausible consequence; local approach; stratified knowledge base

Domains: Computer Science [cs]; Artificial Intelligence [cs.AI]

Salem Benferhat, Didier Dubois, Henri Prade. A local approach to reasoning under inconsistency in stratified knowledge bases. 3rd European conference Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ESCQARU 1995), 1995, Fribourg, Switzerland. pp.36-43. ⟨hal-03299846⟩