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Bayesian incentive compatibility via fractional assignments

Published: 23 January 2011 Publication History

Abstract

Very recently, Hartline and Lucier [14] studied single-parameter mechanism design problems in the Bayesian setting. They proposed a black-box reduction that converted Bayesian approximation algorithms into Bayesian-Incentive-Compatible (BIC) mechanisms while preserving social welfare. It remains a major open question if one can find similar reduction in the more important multi-parameter setting. In this paper, we give positive answer to this question when the prior distribution has finite and small support. We propose a black-box reduction for designing BIC multi-parameter mechanisms. The reduction converts any algorithm into an ε-BIC mechanism with only marginal loss in social welfare. As a result, for combinatorial auctions with sub-additive agents we get an ε-BIC mechanism that achieves constant approximation.

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  1. Bayesian incentive compatibility via fractional assignments

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      cover image ACM Conferences
      SODA '11: Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete algorithms
      January 2011
      1785 pages

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      Society for Industrial and Applied Mathematics

      United States

      Publication History

      Published: 23 January 2011

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      SODA '11
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      SODA '11: 22nd ACM-SIAM Symposium on Discrete Algorithms
      January 23 - 25, 2011
      California, San Francisco

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      Overall Acceptance Rate 411 of 1,322 submissions, 31%

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      • (2024)Settling the Competition Complexity of Additive Buyers over Independent ItemsProceedings of the 25th ACM Conference on Economics and Computation10.1145/3670865.3673627(420-446)Online publication date: 8-Jul-2024
      • (2021)An efficient ε-BIC to BIC transformation and its application to black-box reduction in revenue maximizationProceedings of the Thirty-Second Annual ACM-SIAM Symposium on Discrete Algorithms10.5555/3458064.3458145(1337-1356)Online publication date: 10-Jan-2021
      • (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
      • (2020)Black-box methods for restoring monotonicityProceedings of the 37th International Conference on Machine Learning10.5555/3524938.3525262(3463-3473)Online publication date: 13-Jul-2020
      • (2019)Simple mechanisms for subadditive buyers via dualityACM SIGecom Exchanges10.1145/3331033.333103717:1(39-53)Online publication date: 7-May-2019
      • (2019)The Complexity of Black-Box Mechanism Design with PriorsProceedings of the 2019 ACM Conference on Economics and Computation10.1145/3328526.3329648(869-883)Online publication date: 17-Jun-2019
      • (2019)On Black-Box Transformations in Downward-Closed EnvironmentsTheory of Computing Systems10.1007/s00224-018-9898-663:6(1207-1227)Online publication date: 1-Aug-2019
      • (2018)On simultaneous two-player combinatorial auctionsProceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms10.5555/3174304.3175451(2256-2273)Online publication date: 7-Jan-2018
      • (2018)Simple Mechanisms for a Subadditive Buyer and Applications to Revenue MonotonicityACM Transactions on Economics and Computation10.1145/31054486:3-4(1-25)Online publication date: 1-Oct-2018
      • (2017)Posted pricing sans discriminationProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171642.3171698(388-394)Online publication date: 19-Aug-2017
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