Tools and techniques for automated mechanism design

无论是在授予政府合同还是在商业交易中，拍卖都变得越来越普遍。传统上，博弈论一直被经济学家用来设计拍卖机制，但是，由于各种原因，这些无疑是强大的分析方法并不总是成功或适当的。与此相反，这个项目是探索拍卖设计的计算方法。这个项目集中在两个计算方法。其中之一是共同进化的方法，即机制和参与者交易策略随着时间的推移一起进化。另一种使用强化学习来设置交易策略，然后在给定这些策略的情况下搜索最佳机制。该项目旨在开发这些特定的技术，沿着支持它们的软件工具，使它们能够帮助那些设计拍卖的人，就像计算机辅助设计（CAD）软件包帮助机械工程师和建筑师一样。

Auctions are becoming increasingly common, both in the award of government contracts and in commercial transactions. Traditionally, game theory has been used by economists to design auction mechanisms, but, for various reasons, these undoubtedly powerful analytic methods are not always successful or appropriate. In contrast, this project is exploring computational approaches to auction design.The project focusses on two computational approaches. One of these is a co-evolutionary approach, in which mechanisms and participant trading strategies evolve together over time. The other uses reinforcement learning to set trading strategies and then searches for the best mechanism given these strategies. The project aims to develop these specific techniques along with software tools to support them, towards a point at which they can assist those who design auctions in the same way that computer-aided design (CAD) packages help mechanical engineers and architects.