Robust Mediators in Large Games

Michael Kearns; Mallesh M. Pai; Ryan Rogers; Aaron Roth; Jonathan Ullman

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arXiv · 1512.02698

Robust Mediators in Large Games

Michael Kearns·Mallesh M. Pai·Ryan Rogers·Aaron Roth·Jonathan Ullman

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Abstract

A mediator is a mechanism that can only suggest actions to players, as a function of all agents' reported types, in a given game of incomplete information. We study what is achievable by two kinds of mediators, "strong" and "weak." Players can choose to opt-out of using a strong mediator but cannot misrepresent their type if they opt-in. Such a mediator is "strong" because we can view it as having the ability to verify player types. Weak mediators lack this ability--- players are free to misrepresent their type to a weak mediator. We show a striking result---in a prior-free setting, assuming only that the game is large and players have private types, strong mediators can implement approximate equilibria of the complete-information game. If the game is a congestion game, then the same result holds using only weak mediators. Our result follows from a novel application of differential privacy, in particular, a variant we propose called joint differential privacy.

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BibTeX RIS

Michael Kearns, Mallesh M. Pai, Ryan Rogers, Aaron Roth, Jonathan Ullman. 2015-12-08. Robust Mediators in Large Games. https://arxiv.org/abs/1512.02698

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