Arc and path consistence revisited
Artificial Intelligence
Comments on Mohr and Henderson's path consistency algorithm
Artificial Intelligence
An optimal k-consistency algorithm
Artificial Intelligence
Partial constraint satisfaction
Artificial Intelligence - Special volume on constraint-based reasoning
Semiring-based constraint satisfaction and optimization
Journal of the ACM (JACM)
Maintaining reversible DAC for Max-CSP
Artificial Intelligence
Linear-time algorithms for testing the realisability of line drawings of curved objects
Artificial Intelligence
Path Consistency on Triangulated Constraint Graphs
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Reduction operations in fuzzy or valued constraint satisfaction
Fuzzy Sets and Systems - Optimisation and decision
Arc consistency for soft constraints
Artificial Intelligence
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Path-consistency: when space misses time
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Constraints Between Distant Lines in the Labelling of Line Drawings of Polyhedral Scenes
International Journal of Computer Vision
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Soft arc consistency revisited
Artificial Intelligence
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Valued constraint satisfaction provides a general framework for optimisation problems over finite domains. It is a generalisation of crisp constraint satisfaction allowing the user to express preferences between solutions.Consistency is undoubtedly the most important tool for solving crisp constraints. It is not only a family of simplification operations on problem instances; it also lies at the heart of intelligent search techniques [G. Kondrak, P. van Beek, Artificial Intelligence 89 (1997) 365-387] and provides the key to solving certain classes of tractable constraints [P.G. Jeavons, D.A. Cohen, M.C. Cooper, Artificial Intelligence 101 (1998) 251-265].Arc consistency was generalised to valued constraints by sacrificing the uniqueness of the arc consistency closure [M.C. Cooper, T. Schiex, Artificial Intelligence, in press]. The notion of 3-cyclic consistency, introduced in this paper, again sacrifices the unique-closure property in order to obtain a generalisation of path consistency to valued constraints which is checkable in polynomial time. In MAX-CSP, 3-cyclic consistency can be established in polynomial time and even guarantees a local form of optimality. The space complexity of 3-cyclic consistency is optimal since it creates no new constraints.