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Belief in Belief Functions: An Examination of Shafer's Canonical Examples

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dc.contributor.author Laskey, Kathryn B.
dc.date.accessioned 2006-11-21T18:18:00Z
dc.date.available 2006-11-21T18:18:00Z
dc.date.issued 1989
dc.identifier.citation Laskey, Kathryn B. (1989). Belief in belief functions: An examination of Shafer's canonical examples. In Uncertainty in Artificial Intelligence 3, L.N. Kanal, T.S. Levitt, and J.F. Lemmer, eds., North-Holland. en
dc.identifier.isbn 0-444-88650-8
dc.identifier.uri https://hdl.handle.net/1920/1738
dc.description.abstract In the canonical examples underlying Shafer-Dempster theory, beliefs over the hypotheses of interest are derived from a probability model for a set of auxiliary hypotheses. A belief function differs from a Bayesian probability model in that one does not condition on those parts of the evidence for which no probabilities are specified. The significance of this difference in conditioning assumptions is illustrated with two examples giving rise to identical belief functions but different Bayesian probability distributions.
dc.description.sponsorship Work supported in part by U. S. Army Communications Electronics Command, Contract No. DAAB07-86-C-A052. en
dc.format.extent 444796 bytes
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher North-Holland en
dc.relation.ispartofseries C4I-89-01 en
dc.title Belief in Belief Functions: An Examination of Shafer's Canonical Examples en
dc.type Book chapter en


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