Sangam: A Confluence of Knowledge Streams

A Comparison of Bayesian and Belief Function Reasoning

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dc.creator Cobb, Barry R.
dc.creator Shenoy, Prakash P.
dc.date 2003-12
dc.date 2004-12-14T17:25:06Z
dc.date 2004-12-14T17:25:06Z
dc.date.accessioned 2022-05-18T11:15:32Z
dc.date.available 2022-05-18T11:15:32Z
dc.identifier Information Systems Frontiers, Vol. 5, No. 4, 2003, pp. 345--358
dc.identifier 1387-3326
dc.identifier http://hdl.handle.net/1808/146
dc.identifier https://orcid.org/0000-0002-8425-896X
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/26674
dc.description The goal of this paper is to compare the similarities and differences between Bayesian and belief function reasoning. Our main conclusion is that although there are obvious differences in semantics, representations, the rules for combining and marginalizing representations, there are many similarities. We claim that the two calculi have roughly the same expressive power. Each calculus has its own semantics that allow us to construct models suited for these semantics. Once we have a model in either calculus, one can transform it to the other by means of a suitable transformation.
dc.format 433530 bytes
dc.format application/pdf
dc.language en_US
dc.publisher Kluwer Academic Publishers
dc.rights openAccess
dc.subject Bayesian networks
dc.subject Dempster-Shafer belief function theory
dc.subject Valuation-based systems
dc.title A Comparison of Bayesian and Belief Function Reasoning
dc.type Article


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