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Initialization for the method of conditioning in Bayesian belief networks

✍ Scribed by H.Jacques Suermondt; Gregory F. Cooper

Publisher
Elsevier Science
Year
1991
Tongue
English
Weight
585 KB
Volume
50
Category
Article
ISSN
0004-3702

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✦ Synopsis

Suermondt, H.J. and G.F. Cooper, Initialization for the method of conditioning in Bayesian belief networks (Research Note), Artificial Intelligence 50 (1991) 83-94.

The method of conditioning allows us to use Pearl's probabilistic-inference algorithm in multiply connected belief networks by instantiating a subset of the nodes in the network, the loop cutset. To use the method of conditioning, we must calculate the joint prior probabilities of the nodes of the loop cutset. We present a method that lets us compute these joint priors by instantiating the loop-cutset nodes sequentially.

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