234880

(2016) Synthese 193 (6).

A dilemma for the imprecise bayesian

Namjoong Kim

pp. 1681-1702

Many philosophers regard the imprecise credence framework as a more realistic model of probabilistic inferences with imperfect empirical information than the traditional precise credence framework. Hence, it is surprising that the literature lacks any discussion on how to update one’s imprecise credences when the given evidence itself is imprecise. To fill this gap, I consider two updating principles. Unfortunately, each of them faces a serious problem. The first updating principle, which I call “generalized conditionalization,” sometimes forces an agent to change her imprecise degrees of belief even though she does not have new evidence. The second updating principle, which I call “the generalized dynamic Keynesian model,” may result in a very precise credal state although the agent does not have sufficiently strong evidence to justify such an informative doxastic state. This means that it is much more difficult to come up with an acceptable updating principle for the imprecise credence framework than one might have thought it would be.

Publication details

DOI: 10.1007/s11229-015-0800-7

Full citation:

Kim, N. (2016). A dilemma for the imprecise bayesian. Synthese 193 (6), pp. 1681-1702.

This document is unfortunately not available for download at the moment.