Belief merging using normal forms

Authors:
Pilar Pozos-Parra;Laurent Perrussel;Jean Marc Thevenin
Affiliations:
Department of Informatics and Systems, University of Tabasco, Tabasco, Mexico;Institut de Recherche en Informatique de Toulouse, Université Toulouse I, Toulouse, France;Institut de Recherche en Informatique de Toulouse, Université Toulouse I, Toulouse, France
Venue:
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Year:
2011

Citing 8
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Abstract

Belief merging aims to conciliate multiple possibly inconsistent belief bases into a consistent common belief base. To handle inconsistency some operators have been proposed. Most of them do not consider inconsistent bases. PS-Merge is an alternative method of merging that uses the notion of Partial Satisfiability and allows us to take into account inconsistent bases. PS-Merge needs the bases represented as DNF formulas, nevertheless, many practical problems are easily represented in its CNF. The aim of this paper is to extend the notion of Partial Satisfiability in order to consider bases represented as CNF formulas. Moreover, we consider Prime Normal forms in order to define a method that allows us to implement PS-Merge for difficult theories. We also show that once the belief bases are represented as sets of normal forms, PS-Merge is polynomial.