2005 | OriginalPaper | Buchkapitel
Abstract Model Generation for Preprocessing Clause Sets
verfasst von : Miyuki Koshimura, Mayumi Umeda, Ryuzo Hasegawa
Erschienen in: Logic for Programming, Artificial Intelligence, and Reasoning
Verlag: Springer Berlin Heidelberg
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Abstract model generation refers to model generation for abstract clause sets in which arguments of atoms are ignored. We give two abstract clause sets which are obtained from normal clause sets. One is for checking satisfiability of the original normal clause set. Another is used for eliminating unnecessary clauses from the original one. These abstract clause sets are propositional, i.e. decidable. Thus, we can use them for preprocessing the original one.