Arc and path consistence revisited
Artificial Intelligence
Running efficiently arc consistency
Syntactic and structural pattern recognition
Constraint satisfaction in logic programming
Constraint satisfaction in logic programming
Solving large combinatorial problems in logic programming
Journal of Logic Programming - Logic programming applications
ConstraintLisp: an object-oriented constraint programming language
ACM SIGPLAN Notices
A generic arc-consistency algorithm and its specializations
Artificial Intelligence
Generating Semantic Descriptions From Drawings of Scenes With Shadows
Generating Semantic Descriptions From Drawings of Scenes With Shadows
A generic customizable framework for inverse local consistency
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Functional elimination and 0/1/All constraints
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Efficient Algorithms for Functional Constraints
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Using constraints to model disjunctions in rule-based reasoning
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Solving functional constraints by variable substitution
Theory and Practice of Logic Programming
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Central to solving Constraint Satisfaction Problem (CSP) is the problem of consistency check. Past research has produced many general and specific consistency algorithms. Specific algorithms are efficient specializations of the general ones for specific constraints. Functional, anti-functional and monotonic constraints are three important classes of specific constraints. They form the basis of the current constraint programming languages. This paper proposes a more efficient method for checking an important subclass of functional constraints, increasing functional constraints. Rather than checking them many times as in a typical consistency check process, in the new method they (almost all of them) only need to be checked once. This results in a substantia] saving in computation.