Privacy and Truthful Equilibrium Selection for Aggregative Games

DOI10.1007/978-3-662-48995-6_21zbMath1404.91048arXiv1407.7740OpenAlexW2097264194MaRDI QIDQ3460796

Aaron Roth, Rachel Cummings, Michael Kearns, Zhiwei Steven Wu

Publication date: 8 January 2016

Published in: Web and Internet Economics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1407.7740

zbMATH Keywords

aggregative gamesmechanism designdifferential privacyequilibrium computation

Mathematics Subject Classification ID

Games involving graphs (91A43) (n)-person games, (n>2) (91A06)

Related Items (5)

Privacy and Truthful Equilibrium Selection for Aggregative Games ⋮ Computing payoff allocations in the approximate core of linear programming games in a privacy-preserving manner ⋮ PPAD-complete approximate pure Nash equilibria in Lipschitz games ⋮ PPAD-complete pure approximate Nash equilibria in Lipschitz games ⋮ Scalable and Jointly Differentially Private Packing

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Strong mediated equilibrium
• Mediators in position auctions
• Best-reply dynamics in large binary-choice anonymous games
• Approximately optimal mechanism design via differential privacy
• On the Complexity of Nash Equilibria in Anonymous Games
• Is privacy compatible with truthfulness?
• Mechanism design in large games
• Privacy-Preserving Public Information for Sequential Games
• Privacy and Truthful Equilibrium Selection for Aggregative Games
• Optimal Auction Design
• Privately Solving Linear Programs
• On the complexity of differentially private data release
• Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy)
• Theory of Cryptography

This page was built for publication: Privacy and Truthful Equilibrium Selection for Aggregative Games