We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
Recursive loops in a logic program present a challenging problem to the PLP framework. On the one hand, they loop forever so that the PLP backward-chaining inferences would never s...
Abstract. Dynamic Bayesian networks (DBNs) extend Bayesian networks from static domains to dynamic domains. The only known generic method for exact inference in DBNs is based on dy...
When using Learning Object Repositories, it is interesting to have mechanisms to select the more adequate objects for each student. For this kind of adaptation, it is important to...
Cristina Carmona, Gladys Castillo, Eva Millá...
Abstract— In this paper we consider the problem of sensorimotor coordination in a Bayesian framework. To this end we introduce a novel kind of Dynamic Bayesian Network serving as...
Ruben Coen Cagli, Paolo Napoletano, Paolo Coraggio...