风险下选择的上下文范围依赖模型

IF 2.2 4区 心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Manel Baucells , Michał Lewandowski , Krzysztof Kontek
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引用次数: 0

摘要

我们引入了一种情境依赖的风险选择理论,称为范围效用理论。它建立在心理物理学的Parducci范围原则的基础上,并通过假设风险前景相对于决策环境中所有前景的后果范围进行评估来修改预期效用。当上下文固定时,选择通常表现出风险偏好的四重模式,但与预期效用(概率线性)完全一致,而不调用秩原则。我们在博弈论背景下说明了这一优势。与此同时,当环境发生变化时,选择的相对价值也会发生变化,从而产生不同形式或偏好逆转,其中一些已被有力地记录下来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A contextual range-dependent model for choice under risk

We introduce a context-dependent theory for choice under risk, called range utility theory. It builds on Parducci’s range principle from psychophysics and modifies expected utility by positing that risky prospects are evaluated relative to the range of consequences of all prospects in the decision context. When the context is fixed, choices typically exhibit the four-fold pattern of risk preferences, yet are fully consistent with expected utility (linear in probabilities) without invoking rank-principles. We illustrate this advantage in game theory contexts. As the same time, when the context varies, the relative value of an alternative also does, yielding different forms or preference reversals, some of which have been robustly documented.

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来源期刊
Journal of Mathematical Psychology
Journal of Mathematical Psychology 医学-数学跨学科应用
CiteScore
3.70
自引率
11.10%
发文量
37
审稿时长
20.2 weeks
期刊介绍: The Journal of Mathematical Psychology includes articles, monographs and reviews, notes and commentaries, and book reviews in all areas of mathematical psychology. Empirical and theoretical contributions are equally welcome. Areas of special interest include, but are not limited to, fundamental measurement and psychological process models, such as those based upon neural network or information processing concepts. A partial listing of substantive areas covered include sensation and perception, psychophysics, learning and memory, problem solving, judgment and decision-making, and motivation. The Journal of Mathematical Psychology is affiliated with the Society for Mathematical Psychology. Research Areas include: • Models for sensation and perception, learning, memory and thinking • Fundamental measurement and scaling • Decision making • Neural modeling and networks • Psychophysics and signal detection • Neuropsychological theories • Psycholinguistics • Motivational dynamics • Animal behavior • Psychometric theory
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