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

  • Authors:

  • Leila Amgoud;Souhila Kaci

  • Affiliations:

  • Institut de Recherche en Informatique de Toulouse (I.R.I.T.)–C.N.R.S., Université Paul Sabatier, Toulouse Cedex 4, France;Centre de Recherche en Informatique de Lens (C.R.I.L.)–C.N.R.S., Lens Cedex, France

  • Venue:
  • ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
  • Year:
  • 2005

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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.