Efficient conflict driven learning in a boolean satisfiability solver
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
Towards a Symmetric Treatment of Satisfaction and Conflicts in Quantified Boolean Formula Evaluation
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
sQueezeBF: an effective preprocessor for QBFs based on equivalence reasoning
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
On protection in federated social computing systems
Proceedings of the 4th ACM conference on Data and application security and privacy
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2QBF is a restriction of QBF, in which at most one quantifier alternation is allowed. This simplifying assumption makes the problem easier to reason about, and allows for simpler unit propagation and clause/cube learning procedures. We introduce two new 2QBF algorithms that take advantage of 2QBF specifically. The first improves upon earlier work by Ranjan, Tang, and Malik (2004), while the second introduces a new ‘free' decision heuristic that doesn't need to respect quantifier order. Implementations of both new algorithms perform better than two state-of-the-art general QBF solvers on formal verification and AI planning instances.