Expected Utility Theory

Expected utility theory is the foundational normative framework of modern decision theory. It prescribes that a rational agent should choose the action that maximizes the expected value of a utility function — the probability-weighted average of utility over all possible outcomes. The theory was axiomatized by John von Neumann and Oskar Morgenstern in 1944, who proved that if an agent's preferences satisfy completeness, transitivity, independence, and continuity, then there exists a utility function such that the agent prefers one gamble over another exactly when the first has higher expected utility.

The power of expected utility theory is that it transforms choice under uncertainty into a well-defined optimization problem. The weakness is that its axioms are descriptively false: humans systematically violate independence (the Allais paradox), transitivity (preference reversals), and probability weighting (overweighting small probabilities, underweighting moderate ones). Whether these violations are evidence of human irrationality or of the theory's limited applicability is the central dispute of modern decision research.

The theory remains indispensable as a normative benchmark and as a practical tool in economics, finance, and artificial intelligence. But its dominance has produced a conceptual blind spot: by treating expected utility maximization as the definition of rationality, the field has systematically undervalued decision strategies that are optimal for specific environmental structures rather than universally optimal. The ecological rationality program and the study of bounded rationality are both responses to this blind spot.