发表机构
New York University（纽约大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种度量方法，以彩票与最近退化彩票的距离定义其复杂性，该指数为彩票与其最佳退化近似间的最小平均距离，用于衡量彩票的复杂性。
AI 中文摘要
本文提出了一种度量方法来衡量彩票的复杂性。首先观察到退化彩票是最简单的选择备选方案，某一彩票的复杂性通过它与最近的退化彩票的距离来评估。等价地，当某一彩票难以用单一结果近似时，它就是复杂的。在给定结果上的度量后，我们考虑的复杂性指数是该彩票与其最佳退化近似之一之间的最小平均距离。
英文摘要
We propose a measure of lottery complexity that combines probabilistic dispersion with dissimilarity between outcomes. Taking degenerate lotteries, which yield a single outcome with certainty, as the simplest alternatives, we measure complexity by proximity to this class. Specifically, for each degenerate lottery, we compute the expected distance between its certain outcome and the lottery's outcomes, and take the minimum across all degenerate lotteries. We provide an axiomatic characterization establishing uniqueness up to positive rescaling, study how complexity changes under outcome compression, and characterize maximally complex lotteries. Finally, we introduce Complexity-Adjusted Expected Utility preferences and characterize adherence to stochastic dominance and strong risk aversion.
