Mechanism design in large games

DOI10.1145/2554797.2554834zbMath1364.91010arXiv1207.4084OpenAlexW2166074149MaRDI QIDQ2988894

Mallesh Pai, Aaron Roth, Michael Kearns, Jonathan R. Ullman

Publication date: 19 May 2017

Published in: Proceedings of the 5th conference on Innovations in theoretical computer science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1207.4084

zbMATH Keywords

game theoryequilibrium selectionmechanism designlarge gamedifferential privacy

Mathematics Subject Classification ID

(n)-person games, (n>2) (91A06) Auctions, bargaining, bidding and selling, and other market models (91B26)

Related Items (8)

Privacy and Truthful Equilibrium Selection for Aggregative Games ⋮ Computing payoff allocations in the approximate core of linear programming games in a privacy-preserving manner ⋮ Coopetition Against an Amazon ⋮ Coopetition against an Amazon ⋮ Logarithmic query complexity for approximate Nash computation in large games ⋮ Segmentation, Incentives, and Privacy ⋮ Logarithmic Query Complexity for Approximate Nash Computation in Large Games ⋮ Private Matchings and Allocations

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