Bayesian networks (BNs) have been widely used as a model for knowledge representation and probabilistic inferences. However, the single probability representation of conditional d...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
Abstract— Real-world robotic environments are highly structured. The scalability of planning and reasoning methods to cope with complex problems in such environments crucially de...
When we look at a picture, our prior knowledge about the world allows us to resolve some of the ambiguities that are inherent to monocular vision, and thereby infer 3d information...
Abstract. Mobile devices get to handle much information thanks to the convergence of diverse functionalities. Their environment has great potential of supporting customized service...