Efficient local search for very large-scale satisfiability problems
ACM SIGART Bulletin
GRASP: A Search Algorithm for Propositional Satisfiability
IEEE Transactions on Computers
An Algorithm to Evaluate Quantified Boolean Formulae and Its Experimental Evaluation
Journal of Automated Reasoning
Efficient conflict driven learning in a boolean satisfiability solver
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
SATO: An Efficient Propositional Prover
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
Conflict driven learning in a quantified Boolean Satisfiability solver
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Backjumping for quantified Boolean logic satisfiability
Artificial Intelligence
A satisfiability procedure for quantified boolean formulae
Discrete Applied Mathematics - The renesse issue on satisfiability
Constructing conditional plans by a theorem-prover
Journal of Artificial Intelligence Research
Using CSP look-back techniques to solve real-world SAT instances
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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Emerging applications demand to solve problems that are considered to be more difficult than NP-complete problems. Evaluating a quantified Boolean formula (QBF) is one of those problems. For the satisfiability problem (SAT), the NP-complete subclass of QBF, excellent solvers have been developed. However, research on subclasses of QBF at higher levels has only recently surged. We explore the possibility and potential of local search algorithms, which have been proved to be very successful in the case of SAT. Though local search cannot be applied directly to QBF, we introduce an approach to solve QBF at the second level of the polynomial hierarchy that profits significantly from local search.