Bayesian and Non-Bayesian Evidential Updating.

摘要

Four main results are arrived at in this paper. (1) Closed convex sets of classical probability functions provide a representation of belief that includes the representations provided by Shafer probability mass functions as a special case. (2) The impact of uncertain evidence can be (formally) represented by Dempster conditioning, in Shafer's framework. (3) The impact of uncertain-evidence can be (formally) represented in the framework of convex sets of classical probabilities by classical conditionalization. (4) The probability intervals that result from Dempster/Shafer updating on uncertain evidence are included in (and may be properly included in) the intervals that result form Bayesian updating on uncertain evidence.