Abstract

Although it has been shown that in the general case solving causal networks using maximum entropy techniques is NP-complete, P.C. Rhodes. G.R. Garside and the present author have previously provided correct and efficient algorithms for calculating minimally prejudiced estimates for missing conditional probabilities in causal trees and causal inverted trees with multivalued events. This paper considers multivalued singly connected causal networks (polytrees) and shows that in this case, maximum entropy can be used to find minimally prejudiced estimates for missing information efficiently.

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