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    A Comparison of Bayesian and Belief Function Reasoning

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    ISF03.pdf (423.3Kb)
    Issue Date
    2003-12
    Author
    Cobb, Barry R.
    Shenoy, Prakash P.
    Publisher
    Kluwer Academic Publishers
    Format
    433530 bytes
    Type
    Article
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    Abstract
    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.
    URI
    http://hdl.handle.net/1808/146
    ISSN
    1387-3326
    Collections
    • Distinguished Professors Scholarly Works [918]
    • School of Business Scholarly Works [216]
    Citation
    Information Systems Frontiers, Vol. 5, No. 4, 2003, pp. 345--358

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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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