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风险选择:概率加权解释了猴子违反独立性公理的现象。

Risky choice: Probability weighting explains independence axiom violations in monkeys.

作者信息

Ferrari-Toniolo Simone, Seak Leo Chi U, Schultz Wolfram

机构信息

Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.

出版信息

J Risk Uncertain. 2022;65(3):319-351. doi: 10.1007/s11166-022-09388-7. Epub 2022 Jul 22.

Abstract

UNLABELLED

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 (8%) but substantial graded (46%) between the initial preferred gamble and the corresponding altered gamble. Linear Discriminant Analysis (LDA) indicated that gamble probabilities predicted most 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 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 may reflect the long experience of our monkeys, their more graded 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.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11166-022-09388-7.

摘要

未标注

预期效用理论(EUT)为在风险选择中最大化效用提供了公理。独立性公理(IA)是其最严格的公理:当通过将两个选项与一个共同的赌博进行同等混合来改变这两个选项时,它们之间的偏好不应改变。我们在数月时间里,使用大量二元期权集,对数千个随机选择进行了测试,以检验对IA的共同后果(CC)和共同比率(CR)违背情况。三只猴子始终表现出很少有直接违背(8%),但在初始偏好的赌博和相应改变后的赌博之间存在大量渐变违背(46%)。线性判别分析(LDA)表明,赌博概率在CC(72%)和CR(88%)测试中预测了大部分情况。赤池信息准则表明,累积前景理论(CPT)中的概率加权比使用期望值(EV)或EUT的模型能更好地解释选择。通过CPT的效用和概率加权函数进行拟合,在马尔沙克 - 马基纳三角形中得到了非线性且不平行的无差异曲线(IC)),并表明使用EV或EUT的模型不符合IA。事实上,CPT模型的预测比EV和EUT模型更好。样本外测试中的无差异点比EV和EUT的IC更接近CPT估计的IC。最后,虽然少数直接违背可能反映了我们猴子的长期经验,但它们更多的渐变违背与人类报告的情况相对应。通过利用猴子广泛的测试可能性,我们严格的公理测试为风险决策提供了关键信息,并为研究神经元决策机制奠定了基础。

补充信息

在线版本包含可在10.1007/s11166 - 022 - 09388 - 7获取的补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0af/9840594/6055c829164e/11166_2022_9388_Fig1_HTML.jpg

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