Generating Propagation Rules for Finite Domains: A Mixed Approach
Selected papers from the Joint ERCIM/Compulog Net Workshop on New Trends in Contraints
Automatic Generation of Propagation Rules for Finite Domains
CP '02 Proceedings of the 6th 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
A System for Tabled Constraint Logic Programming
CL '00 Proceedings of the First International Conference on Computational Logic
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
Automatic generation of CHR constraint solvers
Theory and Practice of Logic Programming
Constructing Rule-Based Solvers for Intentionally-Defined Constraints
Constraint Handling Rules
Analysing graph transformation systems through constraint handling rules
Theory and Practice of Logic Programming
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Inductive Constraint Solvingis a subfield of inductive machine learning concerned with the automatic generation of rule-based constraint solvers. In this paper, we propose an approach to generate constraint solvers given the definition of the constraints that combines the advantages of generation by construction with generation by testing. In our proposed approach, semantically valid rules are constructed symbolically, then the constructed rules are used to prune the search tree of a generate and test method. The combined approach leads in general to more expressive and efficient constraint solvers. The generated rules are implemented in the language Constraint Handling Rules.