Partial constraint satisfaction
Artificial Intelligence - Special volume on constraint-based reasoning
Maintaining reversible DAC for Max-CSP
Artificial Intelligence
On Forward Checking for Non-binary Constraint Satisfaction
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
Arc Consistency for Soft Constraints
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Boosting Search with Variable Elimination
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
An Original Constraint Based Approach for Solving over Constrained Problems
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Directed Arc Consistency Preprocessing
Constraint Processing, Selected Papers
Constraint solving over semirings
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Russian doll search for solving constraint optimization problems
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Range-Based Algorithm for Max-CSP
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Bucket elimination for multiobjective optimization problems
Journal of Heuristics
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The necessity of non-binary constraint satisfaction algorithms is increasing because many real problems are inherently nonbinary. Considering overconstrained problems (and Partial Forward Checking as the solving algorithm), we analyze several lower bounds proposed in the binary case, extending them for the non-binary case. We show that techniques initially developed in the context of reversible DAC can be applied in the general case, to deal with constraints of any arity. We discuss some of the issues raised for non-binary lower bounds, and we study their computational complexity. We provide experimental results of the use of the new lower bounds on overconstrained random problems, including constraints with different weights.