Abstract. Although constraint programming offers a wealth of strong, generalpurpose methods, in practice a complex, real application demands a person who selects, combines, and ref...
We propose a generic, domain-independent local search method called adaptive search for solving Constraint Satisfaction Problems (CSP). We design a new heuristics that takes advan...
A team of constraint agents with diverse viewpoints canfind a solution to a constraint satisfaction problem (CSP) whenthe individual agents have an incomplete viewof the problem.I...
We report on the performance of an enhanced version of the “Davis-Putnam” (DP) proof procedure for propositional satisfiability (SAT) on large instances derived from realworld...
We present resolvent-based learning as a new nogood learning method for a distributed constraint satisfaction algorithm. This method is based on a look-back technique in constrain...