Collaborative Research: Data-driven Mechanism Design for Combinatorial Auctions and Exchanges
Collaborative Research: Data-driven Mechanism Design for Combinatorial Auctions and Exchanges
批准号:
1761163
负责人:
Benjamin Lubin
金额:
$27.74万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-08-15 至 2022-07-31
中文摘要
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英文摘要
This award promises to contribute to the nation's economic prosperity by improving the efficiency of market mechanisms. Market mechanisms increase the welfare of market participants by enabling the transfer of goods and services from those who ascribe a low value to their holdings to those who ascribe a higher value to them. Combinatorial auctions and exchanges are market mechanisms that allow agents to specify preferences (via bids and offers) over bundles of assets (goods, services, rights). The value of an item may depend on whether an agent owns a different item, so the value of a bundle of items may differ from the sum of the values of individual items in the bundle. There are many important domains where the need for such mechanisms arise, such as wireless spectrum markets, which transfer radio spectrum rights from governments to mobile phone carriers and between carriers, truckload transportation, and the leasing market for cloud computing resources. Each of these markets involves the transfer of billions of dollars, and in many cases, the assets are publicly owned. The project will involve undergraduate and graduate student training, and will also support the outreach activities of the PIs in organizing college student volunteers to teach STEM subjects to inner-city K-12 public school students. As there are multiple design objectives in the construction of market mechanisms (efficiency, revenue, incentives, simplicity, etc.), there is no single perfect market design involving combinatorial values. Instead, there is a substantial literature in which a large variety of designs have been suggested. What is missing from this literature, however, is a sound methodology for comparing competing designs under realistic models of participants' values. This project addresses this shortcoming by creating a simulation platform that will support data-driven comparisons of combinatorial market designs in the spectrum auction and cloud computing domains. This platform will be open and accessible to the research community, practitioners, and public agencies to rigorously evaluate existing market designs, variations on those designs, and entirely new designs, and to definitively point to features that render some designs better than others in their chosen application domains.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.
期刊论文(4)
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科研奖励(0)
会议论文
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Designing Core-Selecting Payment Rules: A Computational Search Approach
设计核心选择支付规则:一种计算搜索方法
DOI:
10.1287/isre.2022.1108
发表时间:
2022
期刊:
Information Systems Research
影响因子:
4.9
作者:
[Bünz, Benedikt, Lubin, Benjamin, Seuken, Sven]
通讯作者:
Seuken, Sven
DOI:
10.1613/jair.1.11525
发表时间:
2018-12
期刊:
ArXiv
影响因子:
--
作者:
[Vitor Bosshard;Benedikt Bünz;Benjamin Lubin;Sven Seuken]
通讯作者:
Vitor Bosshard;Benedikt Bünz;Benjamin Lubin;Sven Seuken
Fourier Analysis-based Iterative Combinatorial Auctions
基于傅立叶分析的迭代组合拍卖
DOI:
10.24963/ijcai.2022/78
发表时间:
2022
期刊:
Thirty-First International Joint Conference on Artificial Intelligence
影响因子:
--
作者:
[Weissteiner, Jakob, Wendler, Chris, Seuken, Sven, Lubin, Ben, Püschel, Markus]
通讯作者:
Püschel, Markus
iMLCA: Machine Learning-powered Iterative Combinatorial Auctions with Interval Bidding
iMLCA:机器学习驱动的迭代组合拍卖与区间竞价
DOI:
10.1145/3465456.3467535
发表时间:
2021
期刊:
Proceedings of the 22nd ACM Conference on Economics and Computation
影响因子:
--
作者:
[Beyeler, Manuel, Brero, Gianluca, Lubin, Benjamin, Seuken, Sven]
通讯作者:
Seuken, Sven
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