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Published in:
2006 | OriginalPaper | Chapter
Representing Defaults and Negative Information Without Negation-as-Failure
Authors : Pablo R. Fillottrani, Guillermo R. Simari
Published in: Logic for Programming, Artificial Intelligence, and Reasoning
Publisher: Springer Berlin Heidelberg
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In logic programs, negation-as-failure has been used both for representing negative information and for providing default nonmonotonic inference. In this paper we argue that this twofold role is not only unnecessary for the expressiveness of the language, but it also plays against declarative programming, especially if further negation symbols such as strong negation are also available. We therefore propose a new logic programming approach in which negation and default inference are independent, orthogonal concepts. Semantical characterization of this approach is given in the style of answer sets, but other approaches are also possible. Finally, we compare them with the semantics for logic programs with two kinds of negation.