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Jeffrey's Rule of Conditioning

Published online by Cambridge University Press:  01 April 2022

Glenn Shafer
Glenn Shafer*
Affiliation:
Department of Mathematics, University of Kansas
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Abstract

Richard Jeffrey's generalization of Bayes' rule of conditioning follows, within the theory of belief functions, from Dempster's rule of combination and the rule of minimal extension. Both Jeffrey's rule and the theory of belief functions can and should be construed constructively, rather than normatively or descriptively. The theory of belief functions gives a more thorough analysis of how beliefs might be constructed than Jeffrey's rule does. The inadequacy of Bayesian conditioning is much more general than Jeffrey's examples of uncertain perception might suggest. The “parameter α” that Hartry Field has introduced into Jeffrey's rule corresponds to the “weight of evidence” of the theory of belief functions.

Type
Research Article
Information
Philosophy of Science , Volume 48 , Issue 3 , September 1981 , pp. 337 - 362
Copyright
Copyright © 1981 by the Philosophy of Science Association

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