Abstract. In this paper, we revisit the consensus of computational complexity on exact inference in Bayesian networks. We point out that even in singly connected Bayesian networks,...
We present node level primitives for parallel exact inference on an arbitrary Bayesian network. We explore the probability representation on each node of Bayesian networks and eac...
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...