An argumentation framework for merging conflicting knowledge bases: The prioritized case

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Abstract

An important problem in the management of knowledge-based systems is the handling of inconsistency. Inconsistency may appear because the knowledge may come from different sources of information. To solve this problem, two kinds of approaches have been proposed. The first category merges the different bases into a unique base, and the second category of approaches, such as argumentation, accepts inconsistency and copes with it. Recently, a "powerful" approach [7, 8, 13] has been proposed to merge prioritized propositional bases encoded in possibilistic logic. This approach consists of combining prioritized knowledge bases into a new prioritized knowledge base, and then to infer from this. In this paper, we present a particular argumentation framework for handling inconsistency arising from the presence of multiple sources of information. Then, we will show that this framework retrieves the results of the merging operator defined in [7, 8, 13]. Moreover, we will show that an argumentation-based approach palliates the limits, due to the drowning problem, of the merging operator. © Springer-Verlag Berlin Heidelberg 2005.

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Amgoud, L., & Kaci, S. (2005). An argumentation framework for merging conflicting knowledge bases: The prioritized case. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3571 LNAI, pp. 527–538). Springer Verlag. https://doi.org/10.1007/11518655_45

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