25 citations · 69 across the 11 of their papers we have counts for
6 papers · 1 filter
Fairness Incentives for Myopic Agents
Sampath Kannan, Michael Kearns, Jamie Morgenstern +4
We consider settings in which we wish to incentivize myopic agents (such as Airbnb landlords, who may emphasize short-term profits and property safety) to treat arriving clients fa…
Robust Mediators in Large Games
Michael Kearns, Mallesh M. Pai, Ryan Rogers +2
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 achieva…
The Strange Case of Privacy in Equilibrium Models
Rachel Cummings, Katrina Ligett, Mallesh M. Pai +1
We study how privacy technologies affect user and advertiser behavior in a simple economic model of targeted advertising. In our model, a consumer first decides whether or not to b…
An Anti-Folk Theorem for Large Repeated Games with Imperfect Monitoring
Mallesh M. Pai, Aaron Roth, Jonathan Ullman
We study infinitely repeated games in settings of imperfect monitoring. We first prove a family of theorems that show that when the signals observed by the players satisfy a condit…
Privacy and Mechanism Design
Mallesh Pai, Aaron Roth
This paper is a survey of recent work at the intersection of mechanism design and privacy. The connection is a natural one, but its study has been jump-started in recent years by t…
Mechanism Design in Large Games: Incentives and Privacy
Michael Kearns, Mallesh M. Pai, Aaron Roth +1
We study the problem of implementing equilibria of complete information games in settings of incomplete information, and address this problem using "recommender mechanisms." A reco…