Perceptrons Play Repeated Games: New Approach to Bounded Rationality

传统的经济理论认为，决策者没有 限制了他们吸收和处理信息的能力， 计算，或探索替代的影响， 行动方针 然而，在现实中，经济行为人往往面临 这些问题太复杂了，任何人都无法处理。 路上了 因此，重要的是要检查结果是否 传统的模型是鲁棒的，当假设无限 信息能力得到放松。 这个项目的重点是分析一种新的描述方式 限制这种能力。 具体而言，每个决策者都是 由简单的计算机网络代表。 总额 一个网络的计算能力往往超过 个别机器的能力。 小但设计精良 计算机网络可以存储和处理大量的 信息. 复杂性的概念将被正式化， 处理复杂性的能力有限的影响将是 研究了 此外，这些网络还将用于研究 适应性学习过程 在这个框架中获得的一些初步结果是 与现有文献中发现的那些明显不同， 有限理性 因此，有必要进一步开展这项研究 通过批判性地审查现有的工具， 经济主体的信息能力。

Traditional economic theory presumes that decision makers have no limits on their ability to absorb and process information, to carry out calculations, or to explore the implications of alternative courses of action. In reality, however, economic agents often face problems that are too complex for any individual to treat in this way. Therefore, it is important to examine whether the results of traditional models are robust when the assumption of unlimited informational capacity is relaxed. The focus of this project is to analyze a new way of describing limits on this capacity. Specifically, each decision maker is represented by a network of simple computers. The aggregate computational power of a network often exceeds the sum of the capabilities of individual machines. Small but well designed computer networks can store and process substantial amounts of information. Notion of complexity will be formalized, and the implications of limited capacity to handle complexity will be investigated. In addition, such networks will be used to study adaptive learning processes. Some of the initial results obtained in this framework are strikingly different from those found in the existing literature on bounded rationality. It is then essential to further this research by critically reviewing the existing tools for modeling the limited informational capability of economic agents.