research-article

Simple mechanisms for subadditive buyers via duality

Authors:

Mingfei ZhaoAuthors Info & Claims

STOC 2017: Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing

Pages 170 - 183

https://doi.org/10.1145/3055399.3055465

Published: 19 June 2017 Publication History

Abstract

We provide simple and approximately revenue-optimal mechanisms in the multi-item multi-bidder settings. We unify and improve all previous results, as well as generalize the results to broader cases. In particular, we prove that the better of the following two simple, deterministic and Dominant Strategy Incentive Compatible mechanisms, a sequential posted price mechanism or an anonymous sequential posted price mechanism with entry fee, achieves a constant fraction of the optimal revenue among all randomized, Bayesian Incentive Compatible mechanisms, when buyers' valuations are XOS over independent items. If the buyers' valuations are subadditive over independent items, the approximation factor degrades to O(logm), where m is the number of items. We obtain our results by first extending the Cai-Devanur-Weinberg duality framework to derive an effective benchmark of the optimal revenue for subadditive bidders, and then analyzing this upper bound with new techniques.

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Cited By

Derakhshan MRyu EWeinberg SXue EKleinberg RSaban DBergemann D(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
https://dl.acm.org/doi/10.1145/3670865.3673627
Dütting PFeng ZNarasimhan HParkes DRavindranath S(2024)Optimal Auctions through Deep Learning: Advances in Differentiable EconomicsJournal of the ACM10.1145/363074971:1(1-53)Online publication date: 11-Feb-2024
https://dl.acm.org/doi/10.1145/3630749
Jin YLu P(2024)Benchmark-Tight Approximation Ratio of Simple Mechanism for a Unit-Demand Buyer2024 IEEE 65th Annual Symposium on Foundations of Computer Science (FOCS)10.1109/FOCS61266.2024.00082(1251-1259)Online publication date: 27-Oct-2024
https://doi.org/10.1109/FOCS61266.2024.00082
Show More Cited By

Index Terms

Simple mechanisms for subadditive buyers via duality
1. Theory of computation
  1. Theory and algorithms for application domains
    1. Algorithmic game theory and mechanism design
      1. Algorithmic mechanism design

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cover image ACM Conferences

STOC 2017: Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing

June 2017

1268 pages

ISBN:9781450345286

DOI:10.1145/3055399

General Chairs:
Hamed Hatami
McGill University
,
Pierre McKenzie
Université de Montréal
,
Program Chair:
Valerie King
University of Victoria

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Published: 19 June 2017

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Cited By

Derakhshan MRyu EWeinberg SXue EKleinberg RSaban DBergemann D(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
https://dl.acm.org/doi/10.1145/3670865.3673627
Dütting PFeng ZNarasimhan HParkes DRavindranath S(2024)Optimal Auctions through Deep Learning: Advances in Differentiable EconomicsJournal of the ACM10.1145/363074971:1(1-53)Online publication date: 11-Feb-2024
https://dl.acm.org/doi/10.1145/3630749
Jin YLu P(2024)Benchmark-Tight Approximation Ratio of Simple Mechanism for a Unit-Demand Buyer2024 IEEE 65th Annual Symposium on Foundations of Computer Science (FOCS)10.1109/FOCS61266.2024.00082(1251-1259)Online publication date: 27-Oct-2024
https://doi.org/10.1109/FOCS61266.2024.00082
Chawla SGoldner KKarlin AMiller J(2024)Non-Adaptive Matroid Prophet InequalitiesAlgorithmic Game Theory10.1007/978-3-031-71033-9_22(389-404)Online publication date: 3-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-71033-9_22
Boutsikas CDrineas PMertzanidis MPsomas AVerma POh ANaumann TGloberson ASaenko KHardt MLevine S(2023)Refined mechanism design for approximately structured priors via active regressionProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3667217(25185-25194)Online publication date: 10-Dec-2023
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Makur AMertzanidis MPsomas ATerzoglou AOh ANaumann TGloberson ASaenko KHardt MLevine S(2023)On the robustness of mechanism design under total variation distanceProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3666202(1620-1629)Online publication date: 10-Dec-2023
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Curry MSandholm TDickerson JElkind E(2023)Differentiable economics for randomized affine maximizer auctionsProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/293(2633-2641)Online publication date: 19-Aug-2023
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Chen ZHuang ZMajdi DYan ZLeyton-Brown KSamuelson LHartline J(2023)Strong Revenue (Non-)Monotonicity of Single-parameter AuctionsProceedings of the 24th ACM Conference on Economics and Computation10.1145/3580507.3597745(452-471)Online publication date: 9-Jul-2023
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Babaioff MDobzinski SKupfer RLeyton-Brown KSamuelson LHartline J(2023)Simplicity in Auctions Revisited: The Primitive ComplexityProceedings of the 24th ACM Conference on Economics and Computation10.1145/3580507.3597695(153-182)Online publication date: 9-Jul-2023
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Assadi SKher VLi GSchvartzman ALeyton-Brown KSamuelson LHartline J(2023)Fine-Grained Buy-Many Mechanisms Are Not Much Better Than BundlingProceedings of the 24th ACM Conference on Economics and Computation10.1145/3580507.3597662(123-152)Online publication date: 9-Jul-2023
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