Abstract
AbstractThe received model of degrees of belief represents them as probabilities. Over the last half century, many philosophers have been convinced that this model fails because it cannot make room for the idea that an agent’s degrees of belief should respect the available evidence. In its place they have advocated a model that represents degrees of belief using imprecise probabilities (sets of probability functions). This paper presents a model of degrees of belief based on Dempster–Shafer belief functions and then presents arguments for belief functions over imprecise probabilities as a model of evidence-respecting degrees of belief. The arguments cover three kinds of issue: theoretical virtues (simplicity, interpretability and flexibility); motivations; and problem cases (dilation and belief inertia).
Publisher
Springer Science and Business Media LLC
Subject
General Social Sciences,Philosophy
Reference47 articles.
1. Bradley, S. (2019). Imprecise probabilities. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Spring ed.). Metaphysics Research Lab, Stanford University.
2. Bradley, S., & Steele, K. (2014). Uncertainty, learning, and the “problem’’ of dilation. Erkenntnis, 79(6), 1287–1303.
3. Cohen, L. J. (1977). The probable and the provable. Clarendon Press.
4. Dempster, A. P. (1967). Upper and lower probabilities induced by a multivalued mapping. The Annals of Mathematical Statistics, 38(2), 325–339.
5. Dempster, A. P. (1968). A generalization of Bayesian inference. Journal of the Royal Statistical Society, Series B (Methodological), 30, 205–247.