4.3 Article

Risky choice: Probability weighting explains independence axiom violations in monkeys

期刊

JOURNAL OF RISK AND UNCERTAINTY
卷 65, 期 3, 页码 319-351

出版社

SPRINGER
DOI: 10.1007/s11166-022-09388-7

关键词

Choice; Probability; Gamble; Preference reversal

资金

  1. Wellcome Trust [WT 095495, WT 204811]
  2. European Research Council (ERC) [293549]
  3. US National Institutes of Mental Health Conte Center at Caltech (NIMH) [P50MH094258]

向作者/读者索取更多资源

This study tested the Independence Axiom of Expected Utility Theory and found violations of this axiom. By analyzing the probabilities of gambles, it was discovered that Cumulative Prospect Theory provided a better explanation for choices. The monkeys' preference changes were consistent with those reported for humans.
Expected Utility Theory (EUT) provides axioms for maximizing utility in risky choice. The Independence Axiom (IA) is its most demanding axiom: preferences between two options should not change when altering both options equally by mixing them with a common gamble. We tested common consequence (CC) and common ratio (CR) violations of the IA over several months in thousands of stochastic choices using a large variety of binary option sets. Three monkeys showed consistently few outright Preference Reversals (8%) but substantial graded Preference Changes (46%) between the initial preferred gamble and the corresponding altered gamble. Linear Discriminant Analysis (LDA) indicated that gamble probabilities predicted most Preference Changes in CC (72%) and CR (88%) tests. The Akaike Information Criterion indicated that probability weighting within Cumulative Prospect Theory (CPT) explained choices better than models using Expected Value (EV) or EUT. Fitting by utility and probability weighting functions of CPT resulted in nonlinear and non-parallel indifference curves (IC) in the Marschak-Machina triangle and suggested IA non-compliance of models using EV or EUT. Indeed, CPT models predicted Preference Changes better than EV and EUT models. Indifference points in out-of-sample tests were closer to CPT-estimated ICs than EV and EUT ICs. Finally, while the few outright Preference Reversals may reflect the long experience of our monkeys, their more graded Preference Changes corresponded to those reported for humans. In benefitting from the wide testing possibilities in monkeys, our stringent axiomatic tests contribute critical information about risky decision-making and serves as basis for investigating neuronal decision mechanisms.

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