Constraint Programming is a powerful approach for modeling and solving many combinatorial problems, scalability, however, remains an issue in . Abstraction and reformulation techni...
Kenneth M. Bayer, Martin Michalowski, Berthe Y. Ch...
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...
Constraint satisfaction techniques are commonly used for solving scheduling problems, still they are rare in AI planning. Although there are several attempts to apply constraint s...
A constraint satisfaction problem, or CSP, can be reformulated as an integer linear programming problem. The reformulated problem can be solved via polynomial multiplication. If t...
Abstract. Subquadrangles are a natural way in which to represent constraints as they do not restrict any subset of their scope. There are already known methods for converting any g...