Constraint satisfaction using constraint logic programming
Artificial Intelligence - Special volume on constraint-based reasoning
Proving Termination of Constraint Solver Programs
Selected papers from the Joint ERCIM/Compulog Net Workshop on New Trends in Contraints
Automatic Generation of Constraint Propagation Algorithms for Small Finite Domains
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
Towards Inductive Constraint Solving
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Schedulers for rule-based constraint programming
Proceedings of the 2003 ACM symposium on Applied computing
Automatic generation of CHR constraint solvers
Theory and Practice of Logic Programming
Schedulers and redundancy for a class of constraint propagation rules
Theory and Practice of Logic Programming
Constraint solver synthesis using tabled resolution for constraint logic programming
LOPSTR'02 Proceedings of the 12th international conference on Logic based program synthesis and transformation
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A general approach to implement propagation and simplification of constraints consists of applying rules over these constraints. Recently, several proposals have been made to solve finite constraint satisfaction problems by means of automatically generated propagation rules [4, 9, 3]. Since propagation rules do not rewrite constraints but add new ones, the constraint store may contain superfluous constraints. Removing these constraints not only allows saving of space but also decreases the cost of constraint solving. Constraints can be removed using simplification rules. In this paper, we present a method to transform propagation rules into simplification rules using the concept of confluence. The generated rules are implemented in the language Constraint Handling Rules (CHR). An example tak en from the field of digital circuit design shows that our approach is of practical use.