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

Laskey, Kathryn B.

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