Arc and path consistence revisited
Artificial Intelligence
Network-based heuristics for constraint-satisfaction problems
Artificial Intelligence
Tree clustering for constraint networks (research note)
Artificial Intelligence
From local to global consistency
Proceedings of the eighth biennial conference of the Canadian Society for Computational Studies of Intelligence on CSCSI-90
Arc consistency for factorable relations
Artificial Intelligence
Synthesizing constraint expressions
Communications of the ACM
Principles of Database Systems
Principles of Database Systems
An Elimination Algorithm for Functional Constraints
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
Hi-index | 0.00 |
Many works have been carried out to improve search efficiency in CSPs, but few of them treated the semantics of the constraints. In this paper, we expose some properties of two classes of constraints, functional and bijective constraints: we first present conditions under which arc and path consistencies are sufficient to guarantee the existence of a bactrack free solution; we then exhibit classes of polynomial problems, and finally we propose a new method of decomposition for problems containing functional or bijective constraints. An interesting point in this method is that the resolution complexity is known prior to the search.