A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Automatic Generation of Music Programs
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
Pruning for the Minimum Constraint Family and for the Number of Distinct Values Constraint Family
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
The complexity of global constraints
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
The range and roots constraints: specifying counting and occurrence problems
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Generalized arc consistency for global cardinality constraint
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Circuit complexity and decompositions of global constraints
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Decompositions of all different, global cardinality and related constraints
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
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We recently proposed a simple declarative language for specifying a wide range of counting and occurrence constraints. The language uses just two global primitives: the Range constraint, which computes the range of values used by a set of variables, and the Roots constraint, which computes the variables mapping onto particular values. In order for this specification language to be executable, propagation algorithms for the Range and Roots constraints should be developed. In this paper, we focus on the study of the Range constraint. We propose an efficient algorithm for propagating the Range constraint. We also show that decomposing global counting and occurrence constraints using Range is effective and efficient in practice.