Imperfect Play in Games of Incomplete Information: Theory and Experiments

不完全信息博弈中的不完美博弈：理论与实验

• 批准号: 0450712
• 负责人: Thomas Palfrey
• 金额: $ 36.78万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-07-01 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0450712&HistoricalAwards=false
• 关键词: Imperfect; Play; Games; Incomplete; Information

We propose to continue our theoretical and experimental research studying Quantal Response Equilibria (QRE), a statistical model of equilibrium behavior in games. The key feature of the equilibrium is that individuals do not always play best responses to the strategies of their opponents, but play better strategies with higher probability than worse strategies. Here we propose to apply QRE to three different areas of application: auctions, voting, and information aggregation. Several different series of experiments are planned, including large-scale experiments (100+ subjects) to test theoretical predictions about information aggregation and strategic voting in large groups. On the theoretical side, we propose to extend the model to dynamic settings to incorporate learning and repeated play, and to generalize the error structure to allow for correlation across moves. There is also a computational part of the proposal. Specifically, we plan to extend our current algorithms for computing QRE in several ways, to allow more efficient computation of equilibria in certain kinds of larger games and to allow for estimation in models with more general error structures.

我们建议继续我们的理论和实验研究研究数量响应平衡（QRE），这是游戏中平衡行为的统计模型。 平衡的关键特征是，个人并不总是对对手的策略做出最佳反应，而是比更糟糕的策略发挥更好的策略。 在这里，我们建议将QRE应用于三个不同的申请领域：拍卖，投票和信息汇总。 计划了几个不同的实验，包括大规模实验（100多名受试者），以测试有关信息聚集和大型策略投票的理论预测。 在理论方面，我们建议将模型扩展到动态设置，以结合学习和重复播放，并概括误差结构以允许跨移动的相关性。 提案也有一个计算部分。 具体而言，我们计划以几种方式扩展当前的计算QRE算法，以便在某些类型的较大游戏中更有效地计算平衡，并允许在具有更一般错误结构的模型中进行估算。