Uncertainty in Artificial Intelligence
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Similarity Networks for the Construction of Multiple-Fault Belief Networks
David Heckerman
Abstract:
A similarity network is a tool for constructing belief networks for the diagnosis of a single fault. In this paper, we examine modifications to the similarity-network representation that facilitate the construction of belief networks for the diagnosis of multiple coexisting faults.
Keywords: null
Pages: 51-64
PS Link:
PDF Link: /papers/90/p51-heckerman.pdf
BibTex:
@INPROCEEDINGS{Heckerman90,
AUTHOR = "David Heckerman ",
TITLE = "Similarity Networks for the Construction of Multiple-Fault Belief Networks",
BOOKTITLE = "Uncertainty in Artificial Intelligence 6 Annual Conference on Uncertainty in Artificial Intelligence (UAI-90)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1990",
PAGES = "51--64"
}


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