Philosophy of Science 48 (3):337-362 (1981)
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
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Maximum Entropy Inference as a Special Case of Conditionalization.Brian Skyrms - 1985 - Synthese 63 (1):55 - 74.
Languages and Designs for Probability Judgment.Glenn Shafer & Amos Tversky - 1985 - Cognitive Science 9 (3):309-339.
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