BibTeX
@MISC{Kyburg92set-basedbayesianism,
author = {Henry E. Kyburg and Jr. and Michael Pittarelli},
title = {Set-Based Bayesianism},
year = {1992}
}
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Abstract
. Problems for strict and convex Bayesianism are discussed. A set-based Bayesianism generalizing convex Bayesianism and intervalism is proposed. This approach abandons not only the strict Bayesian requirement of a unique real-valued probability function in any decision-making context but also the requirement of convexity for a set-based representation of uncertainty. Levi's E-admissibility decision criterion is retained and is shown to be applicable in the non-convex case. Keywords: Uncertainty, decision-making, maximum entropy, Bayesian methods. 1. Introduction. The reigning philosophy of uncertainty representation is strict Bayesianism. One of its central principles is that an agent must adopt a single, real-valued probability function over the events recognized as relevant to a given problem. Prescriptions for defining such a function for a given agent in a given situation range from the extreme personalism of deFinetti (1964, 1974) and Savage (1972) to the objective Bayesianism of...
