A major challenge in constraint programming is to develop efficient generic approaches to
solve instances of the constraint satisfaction problem (CSP). With this aim in mind, this book …

Constraint satisfaction has been used as a term to cover a wide range of methods to solve
problems stated in the form of a set of constraints. As the general constraint satisfaction …

Constraint programming is a powerful paradigm for solving combinatorial search problems
that draws on a wide range of techniques from artificial intelligence, computer science …

Methods exploiting tree-decompositions seem to provide the best approach for solving
constraint networks wrt the theoretical time complexity. However, they have not shown a real …

Constraint programming is rapidly becoming the technology of choice for modeling and
solving complex combinatorial problems. However, users of constraint programming …

Many attempts have been made to apply machine learning techniques to constraint
satisfaction problems (CSPs). However, none of them have made use of the recent …

In the last twenty years, many algorithms and heuristics were developed to find solutions in
constraint networks. Their number increased to such an extent that it quickly became …

A constraint satisfaction problem (CSP) consists of a set of variables; for each variable, a nite
set of possible values (its domain); and a set of constraints restricting the values that the …

The paper presents a method for generating solutions of a constraint satisfaction problem
(CSP) uniformly at random. Our method relies on expressing the constraint network as a …

Constraint programming (CP) is an emergent software technology for declarative description
and effective solving of large, particularly combinatorial, problems especially in areas of …