Dual viewpoint heuristics for binary constraint satisfaction problems
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Where the really hard problems are
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Balance and filtering in structured satisfiable problems
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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Recently proposed impact based heuristics have been shown to outperform other instances of the first-fail policy such as the common dom and dom/deg heuristics. This paper compares the behaviour of a constraint and a variable centered impact based heuristic and relates it to the amount of constraint propagation inherent to the model of the problem. Additionally, it presents results which suggest that a lookahead impact heuristic we recently proposed might be the best choice for problems with low locality and where constraint propagation plays an important role.