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Backjumping for Quantified Boolean Logic satisfiability

delete2003-04-01
delete35
PRE
AI
E
Enrico Giunchiglia
M
Massimo Narizzano
A
Armando Tacchella
DOI:10.1016/S0004-3702(02)00373-9delete
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摘要

摘要

En 中文
The implementation of effective reasoning tools for deciding the satisfiability of Quantified Boolean Formulas (QBFs) is an important research issue in Artificial Intelligence. Many decision procedures have been proposed in the last few years, most of them based on the Davis, Logemann, Loveland procedure (DLL) for propositional satisfiability (SAT). In this paper we show how it is possible to extend the conflict-directed backjumping schema for SAT to the satisfiability of QBFs: When applicable, conflict-directed backjumping allows search to skip over existentially quantified literals while backtracking. We introduce solution-directed backjumping, which allows the same behavior for universally quantified literals. We show how it is possible to incorporate both conflict-directed and solution-directed backjumping in a DLL-based decision procedure for satisfiability of QBFs. We also implement and test the procedure: The experimental analysis shows that, because of backjumping, significant speed-ups can be obtained. Summing up: We present the first algorithm that applies conflict and solution directed backjumping to QBF, and demonstrate the performance of this algorithm via an empirical study. (C) 2002 Elsevier Science B.V. All rights reserved.
Keyword:
Quantified Boolean Logic
satisfiability testing
automated reasoning
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期刊

Artificial Intelligence Review 封面图
Artificial Intelligence Review
IF:
13.9
论文数:
6.1K
被引数:
1.9W

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