Algorithms for Computing the Equilibrium Payoff Sets of Dynamic Games with Perfect Monitoring

该奖项为计算战略均衡的新方法和算法的研究提供资金。许多经济情况涉及主体之间反复的相互作用。这些重复的战略互动也出现在社会科学的其他领域，包括政治和国际关系。这种互动的最基本形式是重复游戏。这提供了一个数学框架，在这个框架中，持续的互动可以被量化，并且可以同时以一种连贯的方式评估诸如欺骗的短视诱惑、参与者的数量、参与者在计划行动和反应时可获得的信息、当前与未来关注的强迫性等因素的影响。在这一努力中，一个不可或缺的工具是平衡的概念。然而，除了在最平凡的公式中，实际计算可能的平衡是一项困难的任务。即使在相对简单的程式化设置中，社会科学家也很难调查潜在条件变化的影响（如果某些投入的价格发生变化会发生什么，如果限制公司对其竞争对手的信息的法规到位会发生什么，如果贸易关税改变会发生什么，等等）。这个项目直接针对这个计算问题。PI和他的团队试图开发一种方法，可以使用标准的笔记本电脑快速得出答案。初步结果包括一些有前途的新方法。总体目标是将这些结果扩展到其他重要的重复交互类，从而为学生、研究人员和从业者提供重要的新工具，以促进他们对正在进行的交互的分析。

This award funds research in new methods and algorithms for computing strategic equilibria. Many economic situations involve repeated interactions between agents. These repeated strategic interactions also appear in other realms of social science including politics and international relations.The most basic formalization of such interactions is a repeated game. This provides a mathematical framework in which ongoing interactions can be quantified and the impact of such factors as the myopic temptations to cheat, the number of participants, the information available to participants when they plan their moves and responses, the compellingness of present versus future concerns, and so on, can be simultaneously assessed in a coherent way. An indispensable tool in this endeavor is the notion of equilibrium.However, except in the most trivial formulations, the actual computation of possible equilibria is a difficult task. Even in relatively simple stylized settings it is difficult for the social scientist to investigate the impact of changes in underlying conditions (what happens if the price of certain inputs changes, what if regulations are put in place which limit the information firms have about their rivals, what if trade tariffs are altered, and so on). This project aims squarely at this computational problem.The PI and his team seek to develop methods that yield answers rapidly using standard laptop computers. Preliminary results include a number of promising new methods. The overall goal is to extend these results to other important classes of repeated interactions and thereby provide students, researchers and practitioners, important new tools to facilitate their analysis of ongoing interactions.