In constraint programming one models a problem by stating constraints on acceptable solutions. The constraint model is then usually solved by interleaving backtracking search and ...
: In real life scenarios there is often the need for modelling conditional plans where external events determgine the actual execution sequence. Conditional Temporal Problems (CTPs...
Marco Falda, Francesca Rossi, Kristen Brent Venabl...
Abstract. This work considers the problem of approximating fixed predicate constraint satisfaction problems (MAX k-CSP(P)). We show that if the set of assignments accepted by P co...
Inference tasks in Markov random fields (MRFs) are closely related to the constraint satisfaction problem (CSP) and its soft generalizations. In particular, MAP inference in MRF i...
Constraint satisfaction problems (CSPs) provide a model often used in Artificial Intelligence. Since the problem of the existence of a solution in a CSP is an NP-complete task, man...