Uncertainty in Artificial Intelligence
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Cautious Propagation in Bayesian Networks
Finn Jensen
Abstract:
Consider the situation where some evidence e has been entered to a Bayesian network. When performing conflict analysis, sensitivity analysis, or when answering questions like "What if the finding on X had been y instead of x?" you need probabilities P (e'| h), where e' is a subset of e , and h is a configuration of a (possibly empty) set of variables. Cautious propagation is a modification of HUGIN propagation into a Shafer-Shenoy-like architecture. It is less efficient than HUGIN propagation; however, it provides easy access to P (e'| h) for a great deal of relevant subsets e'.
Keywords: Bayesian networks, propagation, fast retraction, sensitivity analysis.
Pages: 323-328
PS Link:
PDF Link: /papers/95/p323-jensen.pdf
BibTex:
@INPROCEEDINGS{Jensen95,
AUTHOR = "Finn Jensen ",
TITLE = "Cautious Propagation in Bayesian Networks",
BOOKTITLE = "Proceedings of the Eleventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-95)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1995",
PAGES = "323--328"
}


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