In this paper, we introduce a new solving algorithm for Constraint Satisfaction Problems (CSP). It performs an overall local search helped with a domain filtering technique to prune the search space. Conflicts detected during filtering are used to guide the search. First experiments with a tabu version of the algorithm have shown good results on hard instances of open shop scheduling problems. It competes well with the best highly specialized algorithms.

This article follows a tutorial, given by the authors on dynamic constraint solving at CP 2003 [87]. It aims at offering an overview of the main approaches and techniques that have been proposed in the domain of constraint satisfaction to deal with uncertain and dynamic environments.

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