Abstract
Inconsistencies may naturally occur in the considered application domains in Artificial Intelligence, for example as a result of data mining works in distributed sources. In order to solve inconsistent knowledge, several paraconsistent description logics have been proposed. In this paper, we face the problem of concept learning for an inconsistent knowledge base system based on bisimulation. This algorithm allows learning a concept from a training information system in a paraconsistent descriptive logic system with a set of positive items, negative items, and inconsistent items. Here, we present a system for learning concept in an inconsistent knowledge base and discuss preliminary experimental results obtained in the electronic application domain.
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