ABSTRACT
The Bayesian approach to decision making under uncertainty prescribes that a decision maker have a unique prior probability and a utility function such that decisions are made so as to maximize the expected utility. In particular, in a statistical inference problem the decision maker is assumed to have a probability distribution over all possible distributions which may govern a certain random process.
