Dual viewpoint heuristics for binary constraint satisfaction problems
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
An Algorithm to Evaluate Quantified Boolean Formulae and Its Experimental Evaluation
Journal of Automated Reasoning
Contradicting Conventional Wisdom in Constraint Satisfaction
PPCP '94 Proceedings of the Second International Workshop on Principles and Practice of Constraint Programming
Beyond NP: Arc-Consistency for Quantified Constraints
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
QCSP made practical by virtue of restricted quantification
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Quantified constraint satisfaction problems: from relaxations to explanations
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Look-ahead value ordering for constraint satisfaction problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Backjumping for quantified Boolean logic satisfiability
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
QCSP-solve: a solver for quantified constraint satisfaction problems
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Reusing CSP propagators for QCSPs
CSCLP'06 Proceedings of the constraint solving and contraint logic programming 11th annual ERCIM international conference on Recent advances in constraints
BlockSolve: a bottom-up approach for solving quantified CSPs
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Realtime online solving of quantified CSPs
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
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We investigate the use of value ordering in backtracking search for Quantified Constraint Satisfaction problems (QCSPs). We consider two approaches for ordering heuristics. The first approach is solution-focused and is inspired by adversarial search: on existential variables we prefer values that maximise the chances of leading to a solution, while on universal variables we prefer values that minimise those chances. The second approach is verification-focused, where we prefer values that are easier to verify whether or not they lead to a solution. In particular, we give instantiations of this approach using QCSP-Solve's pure-value rule Gent et al. (QCSP-solve: A solver for quantified constraint satisfaction problems. In Proceedings of IJCAI, pp. 138---143, 2005). We show that on dense 3-block problems, using QCSP-Solve, the solution-focused adversarial heuristics are up to 50% faster than lexicographic ordering, while on sparse loose interleaved problems, the verification-focused pure-value heuristics are up to 50% faster. Both types are up to 50% faster on dense interleaved problems, with one pure-value heuristic approaching an order of magnitude improvement.