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摘要翻译：
玩家是从数据中学习收益的统计学习者。他们可能对相同的数据有不同的解释，但对一类学习过程有共同的知识。我提出了一个指标来衡量分析师对战略预测的“信心”，基于预测与实现数据一致的概率。主要结果描述了当数据量越来越大时，分析师对给定预测的信心，并为小数据集提供了界限。该方法产生了新的预测，例如，在高维数据下投机性交易更有可能，而在噪声数据下协调不太可能。
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英文标题：
《Games of Incomplete Information Played By Statisticians》
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作者：
Annie Liang
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最新提交年份：
2020
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分类信息：
一级分类：Economics 经济学
二级分类：Theoretical Economics 理论经济学
分类描述：Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括对契约理论、决策理论、博弈论、一般均衡、增长、学习与进化、宏观经济学、市场与机制设计、社会选择的理论贡献。
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一级分类：Computer Science 计算机科学
二级分类：Computer Science and Game Theory 计算机科学与博弈论
分类描述：Covers all theoretical and applied aspects at the intersection of computer science and game theory, including work in mechanism design, learning in games (which may overlap with Learning), foundations of agent modeling in games (which may overlap with Multiagent systems), coordination, specification and formal methods for non-cooperative computational environments. The area also deals with applications of game theory to areas such as electronic commerce.
涵盖计算机科学和博弈论交叉的所有理论和应用方面，包括机制设计的工作，游戏中的学习（可能与学习重叠），游戏中的agent建模的基础（可能与多agent系统重叠），非合作计算环境的协调、规范和形式化方法。该领域还涉及博弈论在电子商务等领域的应用。
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英文摘要：
Players are statistical learners who learn about payoffs from data. They may interpret the same data differently, but have common knowledge of a class of learning procedures. I propose a metric for the analyst's "confidence" in a strategic prediction, based on the probability that the prediction is consistent with the realized data. The main results characterize the analyst's confidence in a given prediction as the quantity of data grows large, and provide bounds for small datasets. The approach generates new predictions, e.g. that speculative trade is more likely given high-dimensional data, and that coordination is less likely given noisy data.
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PDF链接：
https://arxiv.org/pdf/1910.07018
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