Mechanism Design for Fun and Profit

Abstract

The emergence of the Internet as one of the most important arenas for resource sharing between parties with diverse and selfish interests has led to a number of fascinating and new algorithmic problems. In these problems, one must solicit the inputs to each computation from participants (or agents) whose goal is to manipulate the computation to their own advantage. Until fairly recently, failure models in computer science have not dealt the notion of selfish participants who “play by the rules” only when it fits them. To deal with this, algorithms must be designed so as to provide motivation to the participants to “play along”. Recent work in this area, has drawn on ideas from game theory and microeconomics, and specifically from the field of mechanism design. The goal is to design protocols so that rational agents will be motivated to adhere to the protocol. A specific focus has been on truthful mechanisms in which selfish agents are motivated to reveal their true inputs.

In the first part of the talk, we survey recent work in the area of algorithm mechanism design. In the second part of the talk, we focus on mechanism design specifically geared at maximizing the profit of the mechanism designer. In particular, we consider a class of dynamic pricing problems motivated by the same computational and economic trends. We describe a class of generalized auction problems as well as a competitive framework that can be used to evaluate solutions to these problems.We present a number of results on the design of profit-maximizing truthful generalized auctions. This is joint work with Amos Fiat, Andrew Goldberg and Jason Hartline.