Tools and techniques for automated mechanism design

自动化机构设计的工具和技术

• 批准号: 0329037
• 负责人: Simon Parsons
• 金额: --
• 依托单位: CUNY Brooklyn College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0329037&HistoricalAwards=false
• 关键词: Tools; techniques; automated; mechanism; design

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.

拍卖正变得越来越普遍，无论是在授予政府合同时，还是在商业交易中。传统上，经济学家一直使用博弈论来设计拍卖机制，但由于各种原因，这些无疑强大的分析方法并不总是成功或合适的。相反，这个项目正在探索拍卖设计的计算方法。该项目集中在两个计算方法上。其中之一是一种共同进化的方法，即机制和参与者交易策略随着时间的推移一起进化。另一种是使用强化学习来设定交易策略，然后搜索给定这些策略的最优机制。该项目旨在开发这些特定的技术以及支持它们的软件工具，达到这样的程度，即它们可以帮助那些设计拍卖的人，就像计算机辅助设计(CAD)包帮助机械工程师和建筑师一样。