Expected Utility Theory
Updated 2026-08-01
INTRODUCTION
English translation pending.
CORE DEFINITION
Expected utility theory, formalized by John von Neumann and Oskar Morgenstern, holds that a rational agent facing uncertainty should choose the option that maximizes expected utility, computed as the sum over outcomes of each outcome's utility multiplied by its probability. Utility is a subjective measure of value rather than a monetary amount, and a concave utility curve encodes risk aversion. The key qualifier is that it is a normative benchmark for how decisions should be made, not a description of how people decide.
SCAFFOLDING EFFECT
Reduce cognitive load
- Option table: Lay out each alternative, its possible outcomes, and their probabilities before choosing. - Benchmark check: Compare your intuitive choice against the expected-utility ranking to expose bias. - Risk coding: Make your own risk attitude explicit through the shape of your utility curve.
Anchor fast decisions
Decisions under uncertainty cannot be compared by outcomes alone, because each option leads to several possible results. Assigning each result a subjective utility and weighting it by probability produces a single comparable number, so the choice becomes a ranking rather than a guess. The concave shape of the utility function is what makes a sure gain preferable to a gamble of equal expected money, which explains insurance and other risk-averse behavior.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- zh.wikipedia.orghttps://zh.wikipedia.org/wiki/%E9%A2%84%E6%9C%9F%E6%95%88%E7%94%A8%E5%81%87%E8%AF%B4verified
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