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Semantics for Possibilistic Disjunctive Programs*

Published online by Cambridge University Press:  28 July 2011

JUAN CARLOS NIEVES
Affiliation:
Universitat Politècnica de Catalunya, Software Department (LSI), c/Jordi Girona 1-3, E-08034, Barcelona, Spain (e-mail: jcnieves@lsi.upc.edu)
MAURICIO OSORIO
Affiliation:
Universidad de las Américas - Puebla, CENTIA, Sta. Catarina Mártir, Cholula, Puebla, 72820México (e-mail: osoriomauri@gmail.com)
ULISES CORTÉS
Affiliation:
Universitat Politècnica de Catalunya, Software Department (LSI), c/Jordi Girona 1-3, E-08034, Barcelona, Spain (e-mail: ia@lsi.upc.edu)

Abstract

In this paper, a possibilistic disjunctive logic programming approach for modeling uncertain, incomplete, and inconsistent information is defined. This approach introduces the use of possibilistic disjunctive clauses, which are able to capture incomplete information and states of a knowledge base at the same time. By considering a possibilistic logic program as a possibilistic logic theory, a construction of a possibilistic logic programming semantic based on answer sets and the proof theory of possibilistic logic is defined. It shows that this possibilistic semantics for disjunctive logic programs can be characterized by a fixed-point operator. It is also shown that the suggested possibilistic semantics can be computed by a resolution algorithm and the consideration of optimal refutations from a possibilistic logic theory. In order to manage inconsistent possibilistic logic programs, a preference criterion between inconsistent possibilistic models is defined. In addition, the approach of cuts for restoring consistency of an inconsistent possibilistic knowledge base is adopted. The approach is illustrated in a medical scenario.

Type
Regular Papers
Copyright
Copyright © Cambridge University Press 2011

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Footnotes

*

This is a revised and improved version of the following papers: C. Baral, G. Brewka and J. Schipf (Eds), Semantics for possibilistic disjunctive programs appeared in Ninth International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR-07), LNAI 4483; and Semantics for possibilistic disjunctive logic programs in S. Constantini and W. Watson (Eds), Answer Set Programming: Advantage in Theory and Implementation.

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