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Mechanism design via optimal transport

Published: 16 June 2013 Publication History

Abstract

Optimal mechanisms have been provided in quite general multi-item settings [Cai et al. 2012b, as long as each bidder's type distribution is given explicitly by listing every type in the support along with its associated probability. In the implicit setting, e.g. when the bidders have additive valuations with independent and/or continuous values for the items, these results do not apply, and it was recently shown that exact revenue optimization is intractable, even when there is only one bidder [Daskalakis et al. 2013]. Even for item distributions with special structure, optimal mechanisms have been surprisingly rare [Manelli and Vincent 2006] and the problem is challenging even in the two-item case [Hart and Nisan 2012]. In this paper, we provide a framework for designing optimal mechanisms using optimal transport theory and duality theory. We instantiate our framework to obtain conditions under which only pricing the grand bundle is optimal in multi-item settings (complementing the work of [Manelli and Vincent 2006]), as well as to characterize optimal two-item mechanisms. We use our results to derive closed-form descriptions of the optimal mechanism in several two-item settings, exhibiting also a setting where a continuum of lotteries is necessary for revenue optimization but a closed-form representation of the mechanism can still be found efficiently using our framework.

References

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    cover image ACM Conferences
    EC '13: Proceedings of the fourteenth ACM conference on Electronic commerce
    June 2013
    924 pages
    ISBN:9781450319621
    DOI:10.1145/2492002
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    Published: 16 June 2013

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    Author Tags

    1. mechanism design
    2. optimal transport
    3. revenue maximization

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    June 16 - 20, 2013
    Pennsylvania, Philadelphia, USA

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    EC '13 Paper Acceptance Rate 72 of 223 submissions, 32%;
    Overall Acceptance Rate 664 of 2,389 submissions, 28%

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    • (2024)Dynamic Mechanism Design via AI-Driven ApproachesAI-Driven Mechanism Design10.1007/978-981-97-9286-3_3(53-93)Online publication date: 30-Sep-2024
    • (2024)The k-Facility Location Problem via Optimal Transport: A Bayesian Study of the Percentile MechanismsAlgorithmic Game Theory10.1007/978-3-031-71033-9_9(147-164)Online publication date: 31-Aug-2024
    • (2023)Mode connectivity in auction designProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3668426(52957-52968)Online publication date: 10-Dec-2023
    • (2021)The Sample Complexity of Up-to-ε Multi-dimensional Revenue MaximizationJournal of the ACM10.1145/343972268:3(1-28)Online publication date: 22-Mar-2021
    • (2021)Bayesian Auctions with Efficient QueriesArtificial Intelligence10.1016/j.artint.2021.103630(103630)Online publication date: Nov-2021
    • (2020)Robust Auctions for Revenue via Enhanced CompetitionOperations Research10.1287/opre.2019.192968:4(1074-1094)Online publication date: 1-Jul-2020
    • (2019)Automated Mechanism Design via Neural NetworksProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331696(215-223)Online publication date: 8-May-2019
    • (2019)Robustness in Mechanism Design and ContractingAnnual Review of Economics10.1146/annurev-economics-080218-02561611:1(139-166)Online publication date: 2-Aug-2019
    • (2019)Simple mechanisms for subadditive buyers via dualityACM SIGecom Exchanges10.1145/3331033.333103717:1(39-53)Online publication date: 7-May-2019
    • (2019)Simple Mechanisms for Profit Maximization in Multi-item AuctionsProceedings of the 2019 ACM Conference on Economics and Computation10.1145/3328526.3329616(217-236)Online publication date: 17-Jun-2019
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