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- W2111416917 abstract "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." @default.
- W2111416917 created "2016-06-24" @default.
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- W2111416917 date "2005-02-22" @default.
- W2111416917 modified "2023-09-30" @default.
- W2111416917 title "SAT based BDD solver for quantified Boolean formulas" @default.
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- W2111416917 doi "https://doi.org/10.1109/ictai.2004.106" @default.
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