Learning during backtrack search is a space-intensive process that records information (such as additional constraints) in order to avoid redundant work. In this paper, we analyze...
Cooperative distributed problem solving (CDPS) loosely-coupledagentscan be effectively modeledas a distributed constraint satisfaction problem(DCSP) whereeach agent has multiple l...
Constraint Satisfaction Problems (CSP) constitute a convenient way to capture many combinatorial problems. The general CSP is known to be NP-complete, but its complexity depends on...
We study the runtime distributions of backtrack procedures for propositional satisfiability and constraint satisfaction. Such procedures often exhibit a large variability in perfor...
Carla P. Gomes, Bart Selman, Nuno Crato, Henry A. ...
Estimation of Distribution Algorithms (EDAs) are new promising methods in the field of genetic and evolutionary algorithms. In the case of conventional Genetic and Evolutionary Al...