Belief Merging Using Normal Forms

  • Pilar Pozos-Parra
  • Laurent Perrussel
  • Jean Marc Thevenin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7094)

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.

Keywords

Normal Form Conjunctive Normal Form Belief Base Disjunctive Normal Form Propositional Formula 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Pilar Pozos-Parra
    • 1
  • Laurent Perrussel
    • 2
  • Jean Marc Thevenin
    • 2
  1. 1.Department of Informatics and SystemsUniversity of TabascoTabascoMexico
  2. 2.Institut de Recherche en Informatique de ToulouseUniversité Toulouse IToulouseFrance

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