Ploxoma: Testbed for Uncertain Inference

Part of the Lecture Notes in Statistics book series (LNS, volume 112)


This paper compares two formalisms for uncertain inference, Kyburg’s Combinatorial Semantics and Dempster-Shafer belief function theory, on the basis of an example from the domain of medical diagnosis. I review Shafer’s example about the imaginary disease ploxoma and show how it would be represented in Combinatorial Semantics. I conclude that belief function theory has a qualitative advantage because it offers greater flexibility of expression, and provides results about more specific classes of patients. Nevertheless, a quantitative comparison reveals that the inferences sanctioned by Combinatorial Semantics are more reliable than those of belief function theory.


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Copyright information

© Springer-Verlag New York, Inc. 1996

Authors and Affiliations

  • H. Blau
    • 1
  1. 1.Department of Computer ScienceUniversity of RochesterRochesterUSA

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