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Modifiable combining functions1

Published online by Cambridge University Press:  27 February 2009

Paul R. Cohen ,
Glenn Shafer  and
Prakash P. Shenoy
Paul R. Cohen
Affiliation:
Computer and Information Science, University of Massachusetts, Amherst, MA 01003 and School of Business, University of Kansas, Lawrence, KA 66045, U.S.A.
Glenn Shafer
Affiliation:
Computer and Information Science, University of Massachusetts, Amherst, MA 01003 and School of Business, University of Kansas, Lawrence, KA 66045, U.S.A.
Prakash P. Shenoy
Affiliation:
Computer and Information Science, University of Massachusetts, Amherst, MA 01003 and School of Business, University of Kansas, Lawrence, KA 66045, U.S.A.
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Abstract

Modifiable combining functions are a synthesis of two common approaches to combining evidence. They offer many of the advantages of these approaches and avoid some disadvantages. Because they facilitate the acquisition, representation, explanation, and modification of knowledge about combinations of evidence, they are proposed as a tool for knowledge engineers who build systems that reason under uncertainty, not as a normative theory of evidence.

Type
Research Article
Information
AI EDAM , Volume 1 , Issue 1 , February 1987 , pp. 47 - 57
Copyright
Copyright © Cambridge University Press 1987

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