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Applications of a general propagation algorithm for probabilistic expert systems |
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| Authors: | A. P. Dawid |
| Affiliation: | (1) Department of Statistical Science, University College London, Gower Street, WC1 London |
| Abstract: | A probabilistic expert system provides a graphical representation of a joint probability distribution which can be used to simplify and localize calculations. Jensenet al. (1990) introduced a  flow-propagation algorithm for calculating marginal and conditional distributions in such a system. This paper analyses that algorithm in detail, and shows how it can be modified to perform other tasks, including maximization of the joint density and simultaneous fast retraction of evidence entered on several variables. |
| Keywords: | Reasoning under uncertainty causal probabilistic network influence diagram belief network knowledge-based systems evidence fast retraction maxinlization explanation simulation junction tree charge potential function flow propagation |
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