Descriptive Decision Theory
Updated 2026-09-10
INTRODUCTION
English translation pending.
CORE DEFINITION
Descriptive decision theory aims to characterize and explain the regularities in the choices people actually tend to make, in contrast with normative decision theory, which tries to say how people ought to choose. Much work in the area builds and tests formal models that improve on the descriptive adequacy of the subjective expected utility framework, including non-additive probability and multiple priors.
SCAFFOLDING EFFECT
Reduce cognitive load
- Identify bias: compare actual choices with a normative model to find systematic departures. - Predict behavior: use measured regularities to forecast how others will choose under risk. - Attribute error: separate limited ability from different preferences when deciding whether a choice is irrational.
Anchor fast decisions
Subjective expected utility explains choice as maximization under subjective probability and utility, but experiments show systematic departures from its axioms: the Allais paradox exposes the failure of the independence axiom, and ambiguity aversion shows that people do not act on a single probability. Theorists therefore relax probability to non-additive capacities or rank worst cases over sets of priors, improving predictive power.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- plato.stanford.eduhttps://plato.stanford.edu/entries/decision-theory-descriptive/verified
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