This book aims to present an account of rational choice from a
non-Bayesian point of view. Rational agents maximize subjective
expected utility, but contrary to what is claimed by Bayesians, the
author argues that utility and subjective probability should not be
defined in terms of preferences over uncertain prospects. To some
extent, the author’s non-Bayesian view gives a modern account of
what decision theory could have been like, had decision theorists
not entered the Bayesian path discovered by Ramsey, Savage, and
Jeffrey.
The author argues that traditional Bayesian decision theory is
unavailing from an action-guiding perspective. For the deliberating
Bayesian agent, the output of decision theory is not a set of
preferences over alternative acts - these preferences are on the
contrary used as input to the theory. Instead, the output is a (set
of) utility function(s) that can be used for describing the agent
as an expected utility maximizer, which are of limited normative
relevance. On the non-Bayesian view articulated by the author,
utility and probability are defined in terms of preferences over
certain outcomes. These utility and probability functions are then
used for generating preferences over uncertain prospects, which
conform to the principle of maximizing expected utility. It is
argued that this approach offers more action guidance.
