Abstract. SAT Modulo Theories (SMT) consists of deciding the satisfiability of a formula with respect to a decidable background theory, such as linear integer arithmetic, bit-vect...
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
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...
Abstract. We describe a simple CSP formalism for handling multi-attribute preference problems with hard constraints, one that combines hard constraints and preferences so the two a...
Eugene C. Freuder, Robert Heffernan, Richard J. Wa...
Backbone variables have the same assignment in all solutions to a given constraint satisfaction problem; more generally, bias represents the proportion of solutions that assign a v...
Eric I. Hsu, Christian J. Muise, J. Christopher Be...