Proceedings

Stable Model Checking Made Easy

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Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence. Automated Reasoning. Pages 70-74.

Abstract

Disjunctive logic programming (DLP) with stable model semantics is a powerful nonmonotonic formalism for knowledge representation and reasoning. Reasoning with DLP is harder than with normal (V-free) logic programs; because stable model checking - deciding whether a given model is a stable model of a propositional DLP program - is co-NP-complete, while it is polynomial for normal logic programs. This paper proposes a new transformation fM(P), which reduces stable model checking to UNSAT - i.e ., to deciding whether a given CNF formula is unsatisfiable. Thus , the stability of a model M for a program P can be verified by calling a Satisfiability Checker on the CNF formula fM(P). The transformation is parsimonious and efficiently computab le, as it runs in logarithmic space. Moreover, the size of the generated CNF formula never exceeds the size of the input. The proposed approach to stab le model checking ha8 been implemented in a DLP system, and a number of experiments and benchmarks have been run.

Christoph Koch, and Nicola Leone. 1999. Stable Model Checking Made Easy. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI-99. IJCAI, 70–74. https://ijcai.org/proceedings/1999/11
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