A generic arc-consistency algorithm and its specializations
Artificial Intelligence
Arc-consistency and arc-consistency again
Artificial Intelligence
Tractable constraints on ordered domains
Artificial Intelligence
Using constraint metaknowledge to reduce arc consistency computation
Artificial Intelligence
iOpt: A Software Toolkit for Heuristic Search Methods
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Using inference to reduce arc consistency computation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
When do bounds and domain propagation lead to the same search space?
ACM Transactions on Programming Languages and Systems (TOPLAS)
Towards automated reasoning on the properties of numerical constraints
ERCIM'02/CologNet'02 Proceedings of the 2002 Joint ERCIM/CologNet international conference on Constraint solving and constraint logic programming
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Capturing constraint structure is critical in Constraint Programming to support the configuration and adaptation of domain filtering algorithms. To this end, we propose a software model coupling a relational constraint language, a constraint type inference system, and an algorithm configuration system. The relational language allows for expressing constraints from primitive constraints; the type system infers the type of constraint expressions out of primitive constraint types; and the configuration system synthesises algorithms out of primitive routines using constraint types. In this paper, we focus on the issue of constraint type inferencing, and present a method to implement sound and extendible inference systems.