Abstract

In single-person decision theory, Bayesian rationality requires the agent first to attach subjective probabilities to each uncertain event, and then to maximize the expected value of a von Neumann—Morgenstern utility function that is unique up to a cardinal equivalence class. When the agent receives new information, it also requires subjective probabilities to be revised according to Bayes’ rule.