不确定概率理论下的期望效用

Yehuda Izhakian
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引用次数: 57

摘要

将贝叶斯方法推广到不确定概率,提出了一种模糊情况下的决策模型。在这个模型中,对模糊性的偏好与概率直接相关,因此对模糊性的态度被定义为对概率中保持均值的价差的态度——类似于罗斯柴尔德-斯蒂格利茨风险对结果中保持均值价差的态度。该模型细化了品味与信念、风险与模糊性之间的分离。这些分离对于歧义程度的测量以及对歧义态度的引出和表征至关重要,从而提供了一个经验和实验上适用的框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Expected Utility with Uncertain Probabilities Theory
This paper introduces a model of decision making under ambiguity by extending the Bayesian approach to uncertain probabilities. In this model, preferences for ambiguity pertain directly to probabilities such that attitude toward ambiguity is defined as attitude toward mean-preserving spreads in probabilities—analogous to the Rothschild–Stiglitz risk attitude toward mean-preserving spreads in outcomes. The model refines the separations between tastes and beliefs, and between risk and ambiguity. These separations are crucial for the measurement of the degree of ambiguity and for the elicitation and characterization of attitudes toward ambiguity, thereby providing an empirically and experimentally applicable framework.
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