Rational Actor Models

Rational-actor models represent choices using specified preferences, beliefs, and feasible alternatives. Some use expected utility under uncertainty. Preferences can include social concerns, and assumptions about knowledge or computation vary.

Rational-choice models describe an actor selecting a preferred feasible option under specified preferences, beliefs, and constraints. Utility need not mean money or selfishness: concern for other people, rest, or fairness can be part of the preference ordering. Expected-utility maximization under uncertainty is a particular model with additional assumptions, not the definition of every rational-choice account.

The model becomes useful when its inputs constrain a prediction before the choice is observed. A mismatch may reveal a mistaken account of available options, preferences, or beliefs rather than irrationality. Adding a new preference after every surprise can make the explanation fit anything, so ask what future observation would challenge it.

When to use it

When predicting behavior in strategic situations where self-interest dominates; when incentive design needs to anticipate how rational optimizers would respond; when the gap between rational prediction and actual behavior needs explanation; when a baseline analytical model is needed before adding behavioral complexity.

How it can help

Use an explicit choice model to predict behavior, then examine whether errors arise from preferences, beliefs, constraints, or the decision rule. Keep the model testable.