Dynamic Game Theory and Learning

9711885史密斯，本研究对动态博弈论和学习理论做出了方法论和实质性的贡献。它寻求实现未实现的目标，即在完美的信息框架内解释讨价还价的观察到的特征--报价是让步，报价的时间不受限制，交易过程本身就是一场消耗战。它得到了“递归”序贯均衡支付集的刻画，以及后来关于具有隐藏行为和没有汇总公共统计的对策的民间定理。它尽可能地推动了Abreu、Pearce和Stacchetti提出的将动态游戏简化为一次“辅助游戏”的方法。它探索了关于最优实验的一个新猜想--信息需求在后验信念中是准凹的。该模型为探索给定项目研究支出的随机演变提供了一个简单的框架。它在概念上类似于两个博弈论项目，试图通过仔细分析可能继续进行的“游戏”的横截面来理解跨期动态。理解私人信息的动态是博弈论面临的最重要的突出问题之一，在较小程度上，也是契约理论面临的问题。这项研究将开启一大类经济学家目前根本无法解决的模型。它还为建立在动态实验基础上的动态R&D提供了一种简单而实质的新的纯理论。

9711885 Smith This research makes methodological and substantive contributions to dynamic game theory and learning theory. It seeks to attain unmet goals of explaining observed features of bargaining - offers are concessions, timing of offers is unrestricted, the process itself is a war of attrition - in a perfect information framework. It achieves a characterization of the "recursive" sequential equilibrium payoff set, and later a folk theorem for games with hidden actions and no summary public statistic. It pushes as far as possible the methodology introduced by Abreu, Pearce, and Stacchetti of reducing a dynamic game to a one-shot "auxiliary game." It explores a new conjecture about optimal experimentation - that information demand is quasiconcave in the posterior beliefs. The model offers a simple framework for exploring the stochastic evolution of research expenditures on a given project. It is conceptually similar to both game theory projects in the attempt to understand intertemporal dynamics by carefully analyzing the cross-section of possible continuation "games." Understanding the dynamics of private information is one of the single most important outstanding problems facing game theory and, to a lesser extent, contract theory. This research will open up a very large class of models that economists currently simply cannot solve. It also offers a simple and substantive new pure theory of dynamic R&D founded on dynamic experimentation.