An Eecient Algorithm for Nding the M Most Probable Conngurations in Probabilistic Expert Systems
نویسنده
چکیده
A probabilistic expert system provides a graphical representation of a joint probability distribution which enables local computations of probabilities. Dawid (1992) provided a ``ow-propagation' algorithm for nding the most probable connguration of the joint distribution in such a system. This paper analyses that algorithm in detail, and shows how it can be combined with a clever partitioning scheme to formulate an eecient method for nding the M most probable conngurations. The algorithm is a divide and conquer technique, that iteratively identiies the M most probable conngurations. The algorithm has been implemented into the experimental shell XBAIES, which is an extension of BAIES (Cowell, 1992).
منابع مشابه
An efficient algorithm for finding the M most probable configurationsin probabilistic expert systems
A probabilistic expert system provides a graphical representation of a joint probability distribution which enables local computations of probabilities. Dawid (1992) provided a ‘flow-propagation’ algorithm for finding the most probable configuration of the joint distribution in such a system. This paper analyses that algorithm in detail, and shows how it can be combined with a clever partitioni...
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