Uncertainty in Artificial Intelligence
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Minimum Cross Entropy Reasoning in Recursive Causal Networks
Wilson Wen
Abstract:
A probabilistic method of reasoning under uncertainty is proposed based on the principle of Minimum Cross Entropy (MCE) and concept of Recursive Causal Model (RCM). The dependency and correlations among the variables are described in a special language BNDL (Belief Networks Description Language). Beliefs are propagated among the clauses of the BNDL programs representing the underlying probabilistic distributions. BNDL interpreters in both Prolog and C has been developed and the performance of the method is compared with those of the others.
Keywords: null
Pages: 105-119
PS Link:
PDF Link: /papers/88/p105-wen.pdf
BibTex:
@INPROCEEDINGS{Wen88,
AUTHOR = "Wilson Wen ",
TITLE = "Minimum Cross Entropy Reasoning in Recursive Causal Networks",
BOOKTITLE = "Uncertainty in Artificial Intelligence 4 Annual Conference on Uncertainty in Artificial Intelligence (UAI-88)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1988",
PAGES = "105--119"
}


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