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SAT based BDD solver for quantified Boolean formulas

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2 Author(s)
G. Audemard ; CRIL, Univ. d'Artois, Lens, France ; L. Sais

Solving quantified Boolean formulas (QBF) has become an attractive research area in artificial intelligence. Many important artificial intelligence problems (planning, nonmonotonic reasoning, formal verification, etc.) can be reduced to QBFs. A new DLL-based method is proposed that integrates binary decision diagram (BDD) to set free the variable ordering heuristics that are traditionally constrained by the static order of the QBF quantifiers. BDD is used to represent in a compact form the set of models of the Boolean formula. Interesting reduction operators are proposed in order to dynamically reduce the BDD size and to answer the validity of the QBF. Experimental results on instances from the QBF'03 evaluation show that our approach can efficiently solve instances that are very hard for current QBF solvers.

Published in:

Tools with Artificial Intelligence, 2004. ICTAI 2004. 16th IEEE International Conference on

Date of Conference:

15-17 Nov. 2004