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An Algorithm for Finding Minimum dSeparating Sets in Belief Networks
Inference Using Message Propagation and Topology Transformation
An Alternative Markov Property for Chain Graphs
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abstraction action agent algorithm applied approach approximation Artificial Intelligence assignment assume Bayesian network belief networks bounds called combination complexity compute conditional consider consistent constraint construction contains corresponding decision defined Definition denote depends described developed directed distribution edge elements equivalent estimate evaluation evidence example expected extend Figure function given goal graph independence inference joint knowledge learning logic lower Markov means measure method node normal Note observations obtained operator optimal parameters parents path Pearl performance plausibility possible preferences present prior probabilistic probability probability distribution problem procedure random reasoning relation relative representation represented rules sample satisfies selected separator shown similar situation space specific step structure subset Theorem theory tion tree true uncertainty utility variables