The ability to reduce either the number of variables or clauses in instances of the Satisfiability problem (SAT) impacts the expected computational effort of solving a given instan...
We are interested in the expressiveness of constraints represented by general first order formulae, with equality as unique relation symbol and function symbols taken from an infi...
This paper addresses the interaction between randomization, with restart strategies, and learning, an often crucial technique for proving unsatisfiability. We use instances of SAT ...
Abstract. In this paper we propose an optimal anytime version of constrained simulated annealing (CSA) for solving constrained nonlinear programming problems (NLPs). One of the goa...
Constraint programming offers a variety of modeling objects such as logical and global constraints, that lead to concise and clear models for expressing combinatorial optimization...
We perform a comprehensive theoretical and empirical study of the benefits of singleton consistencies. Our theoretical results help place singleton consistencies within the hierar...
Combinatorial problems can be efficiently tackled with constraint programming systems. The main tasks of the development of a constraint-based application are modeling the proble...
The Constraint-Based Agent (CBA) framework is a set of tools for designing, simulating, building, verifying, optimizing, learning and debugging controllers for agents embedded in a...