AF: Small: Computer Science and Decision Making

EBay、谷歌和其他机构的自动化经济交易系统越来越多地谈判、买卖商品、服务、广告等。它们使用拍卖来做出决定，包括定价、分配和优化。因此，我们现在的拍卖系统的规模远远超过传统的谈判和专门拍卖的“人的规模”，它们以复杂的方式影响着我们的生活。这些系统在经济学、学习理论和最优化的界面上面临着许多算法挑战，这是本项目的重点。在本项目中，研究人员将(A)设计和分析各方(用户、拍卖商、买家和卖家)的模型及其对拍卖的影响；(B)在存在混合效用的情况下设计和分析机制，这些机制超越了传统的线性利润；(C)量化机制中预算对真实性、均衡性和效用的影响，这是传统上被忽视的；(D)研究有限计算能力和理性对机制的影响；(E)为期货、组合商品以及动态环境设计更丰富的机制；(F)研究拍卖机制的私密性、安全性和可验证性；(G)研究对上述任务至关重要的各种学习和优化问题。本项目最终解决具有自然旋钮(预算、公用事业)的各方如何与自动经济交易系统互动，如何在这种系统中学习、使用和控制信息，以及这些系统将如何长期发展。该项目通过上述具体的研究任务，以及通过培训本科生和研究生在经济学、最优化和其他领域的接口工作来探索这些问题。

Increasingly, automated economic transaction systems in eBay, Google and other institutions negotiate, buy and sell goods, services, advertisements etc. They use auctions to make decisions including pricing, allocation and optimization. As a result, we now have auctions systems far greater in scale than the traditional "human scale" of negotiations and specialized auctions, and they impact our lives in sophisticated ways. These systems face many algorithmic challenges in the interface of Economics, Learning Theory, and Optimization, which is the focus of this project.In this project researchers will (a) design and analyze models for the various parties (users, auctioneer, buyer and seller) and their impact on the auctions; (b) design and analyze mechanisms in the presence of parties with mixed utilities that go beyond the traditional linear profit; (c) quantify impacts of budgets in mechanisms on truthfulness, equilibria and utilities, which has been traditionally underemphasized; (d) study the effect of bounded computational power and rationality on mechanisms; (e) design richer mechanisms for futures, combinatorial goods as well as dynamic settings; (f) study privacy, security and verifiability of auction mechanisms; (g) study the various learning and optimization problems that are fundamental to the tasks above.This project ultimately addresses the questions of how various parties with natural knobs (budget, utility) interact with automated economic transaction systems, how information is learned, used and controlled in such systems, and how these systems will evolve over the long term. The project explores these questions via the specific research tasks above, as well as via training undergraduate and graduate students to work in the interface of Economics, Optimization and other areas.