Bayesian Decision Theory and Stochastic Independence

TARK 2017 (2017)
  Copy   BIBTEX

Abstract

Stochastic independence has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory. Bayesian decision theorists such as Savage can be criticized for being silent about stochastic independence. From their current preference axioms, they can derive no more than the definitional properties of a probability measure. In a new framework of twofold uncertainty, we introduce preference axioms that entail not only these definitional properties, but also the stochastic independence of the two sources of uncertainty. This goes some way towards filling a curious lacuna in Bayesian decision theory.

Author's Profile

Philippe Mongin
Last affiliation: Centre National de la Recherche Scientifique

Analytics

Added to PP
2017-10-20

Downloads
477 (#37,041)

6 months
85 (#56,866)

Historical graph of downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.
How can I increase my downloads?