ITR/AP:Computer Test Beds and Mechanism Design

机制允许信息分散的个人实现预期的群体结果。 实验证实了理论预测，不同的参数值和不同的机制规则可以有重要影响的结果的效率和收敛速度。将开发一个基于计算机的行为模型，以测试各种机制和机构。 该模型是基于进化算法。 每个智能代理都有一系列不同的策略用于其决策过程。策略通过基于对每个策略的假设和实际性能的评估的选择过程来竞争代理决策的权利。该模型将首先调整机制，有重要的实验数据。 这方面的例子包括Groves-Ledyard机制、公益物自愿捐助机制、双向拍卖以及在一系列平行市场中同时进行交易。然后，该模型将用于预测那些尚未在人类受试者实验中测试的机制下的行为。该项目将为经济学研究开发一种新的方法，这种方法有可能比实验经济学更好，更快，更便宜。

Mechanisms allow individuals with dispersed information to achieve desired group outcomes. Experiments confirm theoretical predictions that different parameter values and different mechanism rules can have important effects on the efficiency of outcomes and the speed of convergence. A computer-based behavioral model will be developed to test a wide range of mechanisms and institutions. The model is to be based on evolutionary algorithms. Each smart agent has a collection of different strategies to use in its decision-making processes. Strategies compete for the right to make agent decisions through a selection process based on an evaluation of each strategy's hypothetical and actual performance. The model will first be tuned with mechanisms for which there are significant experimental data. Examples include the Groves-Ledyard mechanism, the voluntary contribution mechanism for public goods, the double auction, and simultaneous trading in a set of parallel markets. Then the model will be used to make predictions about behavior under those mechanisms that have not already been tested in experiments with human subjects. This project will develop a new methodology for economics research that has potential to be better, faster, and cheaper than experimental economics.