On computing minimal models

Authors:
Rachel Ben-Eliyahu;Rina Dechter
Affiliations:
Cognitive Systems Laboratory, Computer Science Department, University of California, Los Angeles, California;Information & Computer Science, University of California, Irvine, California
Venue:
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Year:
1993

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Abstract

This paper addresses the problem of computing the minimal models of a given CNF propositional theory. We present two groups of algorithms. Algorithms in the first group are efficient when the theory is almost Horn, that is, when there are few non-Horn clauses and/or when the set of all literals that appear positive in any non-Horn clause is small. Algorithms in the other group are efficient when the theory can be represented as an acyclic network of low-arity relations. Our algorithms suggest several characterizations of tractable subsets for the problem of finding minimal models.