Formalizing Risky Choice with a Logistic Model of Fuzzy Trace Theory

Abstract

We propose a new model of risk preferences that integrates theoretical principles relevant to mental representation, metacognitive monitoring and editing, and individual differences in risk-taking propensity. Our model is based on fuzzy-trace theory, a theory of decision-making under risk. The theory posits that decision-makers use fuzzy gist representations of the meaning of decision information, in parallel with precise verbatim representations of the exact wording of that information. We account for core phenomena in decision theory, such as shifts in risk preference when logically equivalent gambles are described in terms of gains rather than losses—framing effects—and also extend fuzzy-trace theory beyond these phenomena to encompass research on affect and personality.


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