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Computer Science Colloquia

*Data Science Institute Distinguished Speaker Series**

Jason Hartline, Associate Professor, Northwestern University

Monday, January 27, 2014

3:30 PM, Rice Hall, Rm. 130 (Light refreshments after the seminar Rice Hall 4th floor atrium)

HOSTS: abhi shelat

Mechanism Design and Economic Inference


Good economic mechanisms depend on the preferences of participants in the mechanism. For example, the revenue-optimal auction for selling an item is parameterized by a reserve price, and the appropriate reserve price depends on how much the bidders are willing to pay. A mechanism designer can potentially learn about the participantsÂ’ preferences by observing historical data from the mechanism; the designer could then update the mechanism in response to learned preferences to improve its performance. The challenge of such an approach is that the data correspond to the actions of the participants and not their preferences. Preferences can be inferred from actions but the degree of inference possible depends on the mechanism. In the optimal auction example, it is impossible to learn anything about preferences of bidders who are not willing to pay the reserve price. These bidders will not cast bids in the auction and, from historical bid data, the auctioneer could never learn that lowering the reserve price would give a higher revenue (even if it would). To address this impossibility, the auctioneer could sacrifice revenue-optimality in the initial auction to obtain better inference properties so that the auction's parameters can be adapted to changing preferences in the future. The goal of this talk is to develop a theory for optimal mechanism design subject to good inferability.

Bio: Jason Hartline is an Associate Professor in Electrical Engineering and Computer Science at Northwestern University. Before joining the faculty at Northwestern, he was a researcher at Microsoft Research, Silicon Valley from 2004 to 2007, where his research covered foundational topic of algorithmic mechanism design and applications

Dr. Hartline's current research interests lie in the intersection of the fields of theoretical computer science, game theory, and economics. With the Internet developing as the single most important arena for resource sharing among parties with diverse and selfish interests, traditional algorithmic and distributed systems approaches are insufficient. Instead, in protocols for the Internet, game-theoretic and economic issues must be considered. A fundamental research endeavor in this new field is the design and analysis of auction mechanisms and pricing algorithms. He has joint work with Shuchi Chawla and Denis Nekipelov.

* This seminar is sponsored by the Data Science Institute, The Department of Computer Science, and the Department of Economics