We propose a new method for solving structured CSPs which generalizes and improves the Cyclic-Clustering approach [4]. First, the cutset and the tree-decomposition of the constrai...
Constraint programming is rapidly becoming the technology of choice for modeling and solving complex combinatorial problems. However, users of constraint programming technology nee...
In this paper we present and evaluate an evolutionary approach for learning new constraint satisfaction algorithms, specifically for MAX-SAT optimisation problems. Our approach of...
Many problem-solving tasks can be formalized as constraint satisfaction problems (CSPs). In a multi-agent setting, information about constraints and variables may belong to differ...
While many real-world combinatorial problems can be advantageously modeled and solved using Constraint Programming, scalability remains a major issue in practice. Constraint models...
Kenneth M. Bayer, Martin Michalowski, Berthe Y. Ch...