Abstract
Both in classical logic and in Answer Set Programming, inconsistency is characterized by non existence of a model. Whereas every formula is a theorem for inconsistent set of formulas, an inconsistent program has no answer. Even if these two results seem opposite, they share the same drawback: the knowledge base is useless since one can not draw valid conclusions from it. Possibilistic logic is a logic of uncertainty able to deal with inconsistency in classical logic. By putting on every formula a degree of certainty, it defines a way to compute, with regard to these degrees, a consistent subset of formulas that can be then used in a classical inference process. In this work, we address the treatment of inconsistency in Answer Set Programming by a possibilistic approach that takes into account the non monotonic aspect of the framework.
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Nicolas, P., Garcia, L., Stéphan, I. (2005). A Possibilistic Inconsistency Handling in Answer Set Programming. In: Godo, L. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2005. Lecture Notes in Computer Science(), vol 3571. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11518655_35
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DOI: https://doi.org/10.1007/11518655_35
Publisher Name: Springer, Berlin, Heidelberg
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