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Semantics for Possibilistic Disjunctive Programs*
Published online by Cambridge University Press: 28 July 2011
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.
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- Regular Papers
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- Copyright © Cambridge University Press 2011
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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