Stochastic Choice and Revealed Perturbed Utility
研究扰动效用函数如何刻画随机选择行为，提出两种简单条件来表征该函数，并探讨选择规则的选择性与扰动性质的关系，对理解不确定性下的决策有用。
Perturbed utility functions—the sum of expected utility and a nonlinear perturbation function—provide a simple and tractable way to model various sorts of stochastic choice. We provide two easily understood conditions each of which characterizes this representation: One condition generalizes the acyclicity condition used in revealed preference theory, and the other generalizes Luce’s IIA condition. We relate the discrimination or selectivity of choice rules to properties of their associated perturbations, both across different agents and across decision problems. We also show that these representations correspond to a form of ambiguity-averse preferences for an agent who is uncertain about her true utility.