Randomization and Ambiguity Aversion
提出一个偏好模型，其中随机化对模糊的影响取决于未知概率法则的确定方式，通过放松Anscombe和Aumann的公理，得到个体拥有一组先验集集合的表示，说明随机化如何部分消除模糊效应。
We propose a model of preferences in which the effect of randomization on ambiguity depends on how the unknown probability law is determined. We adopt the framework of Anscombe and Aumann (1963) and relax the axioms. In the resulting representation of the individual's preference, the individual has a collection of sets of priors <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mi mathvariant="script">M</a:mi> </a:math>. She believes that before she moves, nature has chosen an unknown scenario (a set of priors) from <d:math xmlns:d="http://www.w3.org/1998/Math/MathML" display="inline"> <d:mi mathvariant="script">M</d:mi> </d:math>, and from that scenario, nature will choose a prior after she moves. The representation illustrates how randomization may partially eliminate the effect of ambiguity.