The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...
We present a technique for computing approximately optimal solutions to stochastic resource allocation problems modeled as Markov decision processes (MDPs). We exploit two key pro...
Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, L...
Third Generation (3G) cellular networks utilize timevarying and location-dependent channel conditions to provide broadband services. They employ opportunistic scheduling to effic...
Dynamic detection and elimination of symmetry in constraints, is in general a hard task, but in Not-Equals binary constraint networks, the symmetry conditions can be simplified. I...
Constraint programming is rapidly becoming the technology of choice for modelling and solving complex combinatorial problems. However, users of this technology need significant ex...