RI: Small: Agent-Assisted Trading in Real-World Auctions

RI：小型：现实世界拍卖中的代理辅助交易

• 批准号: 1217761
• 负责人: Amy Greenwald
• 金额: $ 45万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1217761&HistoricalAwards=false
• 关键词: RI; Small; Agent; Assisted; Trading

In many large economic markets, goods are sold through auctions. Examples include eBay, wireless spectrum auctions, the New York Stock Exchange, and the Dutch flower auctions. This project focuses on one particular real-world auction domain: the Dutch flower auctions (DFA). The project will perform an in-depth analysis of this domain both from the point of view of the bidders and from the point of view of the auctioneers.This project involves several component tasks. (1) Creation of a configurable auction server, comprised of basic auction building blocks, like simultaneous and sequential auctions, and sealed-bid, ascending, and descending auctions. (2) Construction of an interactive DFA simulation using the configurable auction server that is capable of handling decisions made by both human bidders and autonomous agents; this simulation will model DFA bidder preferences, which will be learned automatically using inverse reinforcement learning techniques from historical data and manually by surveying and interviewing DFA experts. (3) Creation of autonomous DFA bidding agents and comparison of their performance to that of expert human DFA bidders using the interactive simulation. (4) Further simulation of these agents to empirically find game-theoretic equilibria under various settings of the auction parameters so that those parameters can be optimized. The project will also develop a prototype of a mixed-initiative system that can be used to assist DFA bidders.Potential broader impacts of this research include increased knowledge and understanding of how to design and implement artificially intelligent agents that can effectively assist humans with their decision-making efforts, particularly in information-rich and time-critical environments. Although this project focuses on DFA-type auctions, methodologies developed here will transfer to other domains that use auction mechanisms, such as automated bidding for resource allocation in smart grids. Detailed focus on the DFA provides a concrete starting point for the study of various auction-related topics, for instance, how to build mixed-initiative decision support tools to improve the quality of bidding practices, rigorous comparison of various auction mechanisms and parameter choices, and advancing bidding agent design from a heuristic approach to one that is theoretically grounded.The project research team includes both graduate and undergraduate students whose participation in this research will strengthen their understanding of the various fields that are critical to the development of decision support systems (e.g., autonomous agents, preference elicitation and representation, machine learning, software engineering) and provide them experience collaborating across disciplines, and working on a real-world application. In addition, there are plans to develop introductory lessons on the general topic of autonomous bidding agents for use in the Artemis project, a five week summer program in which female rising ninth graders are exposed to the breadth of applications of computer science, and are introduced to a variety of technologies underlying computing.

在许多大型经济市场中，商品是通过拍卖出售的。例如eBay、无线频谱拍卖、纽约证券交易所和荷兰鲜花拍卖。该项目专注于一个特定的现实世界拍卖领域：荷兰鲜花拍卖(DFA)。该项目将从投标人和拍卖商的角度对这一领域进行深入分析。(1)创建可配置的拍卖服务器，包括基本的拍卖构建块，如同时和顺序拍卖，以及密封出价、递增和递减拍卖。(2)使用可配置的拍卖服务器构建交互式DFA模拟，该模拟能够处理人工投标人和自主代理做出的决策；该模拟将模拟DFA投标人的偏好，该模型将使用反向强化学习技术从历史数据中自动学习，并通过调查和采访DFA专家来手动学习。(3)建立自主的DFA竞价代理，并利用交互仿真将它们的性能与专家人类DFA竞价代理的性能进行比较。(4)进一步对这些代理进行模拟，以求在不同的拍卖参数设置下找到博弈论均衡，从而对这些参数进行优化。该项目还将开发一个可用于帮助DFA投标人的混合倡议系统的原型。这项研究的潜在更广泛影响包括增加了对如何设计和实现人工智能代理的知识和理解，这些代理可以有效地帮助人类进行决策，特别是在信息丰富和时间紧迫的环境中。虽然这个项目关注的是DFA类型的拍卖，但这里开发的方法将转移到使用拍卖机制的其他领域，例如智能电网中资源分配的自动竞价。对DFA的详细关注为各种与拍卖相关的主题的研究提供了一个具体的起点，例如，如何建立混合主动决策支持工具来提高投标实践的质量，对各种拍卖机制和参数选择进行严格的比较，以及将投标代理设计从启发式方法推进到具有理论基础的方法。项目研究团队包括研究生和本科生，他们参与这项研究将加深他们对决策支持系统开发的各个关键领域(如自主代理、偏好诱导和表征、机器学习、软件工程)的理解，并为他们提供跨学科协作的经验。以及开发一个真实世界的应用程序。此外，还计划开发用于Artemis项目的自主竞价代理一般主题的入门课程。Artemis项目是一个为期五周的暑期项目，在该项目中，正在升入九年级的女性将接触到计算机科学的广泛应用，并了解各种基础计算技术。