AF: Medium:Algorithmic Market Design

AF：媒介：算法市场设计

• 批准号: 2312156
• 负责人: Itai Ashlagi
• 金额: $ 120万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2312156&HistoricalAwards=false
• 关键词: AF; Medium; Algorithmic; Market; Design

This project investigates the development of algorithmic foundations to address challenges in real-world markets in which matching is an essential activity. The proposal addresses timely challenges in organ allocation, kidney exchange, student assignment systems, and other matching marketplaces, enriching the mathematically grounded algorithms for resource allocation and matching. The project serves the national interest by promoting scientific progress, advancing market design knowledge, addressing equity and fairness in resource allocation, and enhancing societal welfare. The project will also train undergraduate and graduate students.The research project will address the following areas: algorithmic questions in labor markets, student assignment systems, organ allocation challenges, and algorithmic market design questions in transportation. The project will study the role of information and learning, preference discovery, and equity in matching markets. The project will explore the interaction between algorithms and information towards reducing congestion in entry-level labor markets. In organ allocation, the team will design algorithms for allocating hard-to-place organs, addressing novel algorithmic questions related to online matching and trade-offs between utilization and welfare. The project will also investigate token systems for incentivizing participation of hospitals in kidney exchange platforms. Lastly, it will tackle matching and pricing questions in transportation markets, developing a unifying framework for congestion pricing and carpooling. By integrating algorithms and application understanding, the project seeks to develop grounded solutions for resource allocation and matching, making it both intellectually and practically impactful.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目研究了算法基础的发展，以应对现实世界市场中的挑战，其中匹配是一项必不可少的活动。该提案解决了器官分配、肾脏交换、学生分配系统和其他匹配市场中的及时挑战，丰富了资源分配和匹配的数学基础算法。该项目通过促进科学进步，提高市场设计知识，解决资源配置的公平和公平，提高社会福利，为国家利益服务。该项目还将培养本科生和研究生。该研究项目将涉及以下领域：劳动力市场中的算法问题、学生分配系统、器官分配挑战以及交通运输中的算法市场设计问题。该项目将研究信息和学习、偏好发现和公平在匹配市场中的作用。该项目将探索算法和信息之间的相互作用，以减少入门级劳动力市场的拥堵。在器官分配方面，该团队将设计用于分配难以放置的器官的算法，解决与在线匹配和利用与福利之间权衡相关的新算法问题。该项目还将研究代币系统，以激励医院参与肾脏交换平台。最后，它将解决交通市场的匹配和定价问题，为拥堵定价和拼车制定一个统一的框架。通过整合算法和应用理解，该项目寻求开发资源分配和匹配的基础解决方案，使其在智力和实践上都具有影响力。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。