Incentive Centered Design

Making the Internet Safe, Fun, and Profitable

STIET News

 In the News: Recent STIET PhD Eytan Bakshy's paper "The Role of Social Networks in Information Diffusion" is getting a lot of attention -- see Tech Crunch and Slate.

 News Note: WSU STIET faculty member, Robert Reynolds, STIET fellow Leonard Kinniard-Heether, and REU student Tracy Liu won first place in the IEEE Super Mario Competition and best student paper prize at the 2010 IEEE World Congress on Computational Intelligence in Barcelona, Spain.

 Press Release -- World Wide Research Reshaping the Sciences and Humanities, edited by William H. Dutton and Paul W. Jeffreys includes contributions by STIET faculty member, Steve Jackson, and STIET fellow, Cory Knobel.

Contact STIET

STIET Program
University of Michigan
3373 North Quad
105 S. State St.
Ann Arbor, MI 48109-1285
voice (734) 647-6333
fax (734) 615-3587

User login

Home
» Jan 22 Seminar: Michael Wellman

Jan 22 Seminar: Michael Wellman

Date: 
Thu, 01/22/2009 - 11:00am - 12:30pm
Seminar Information: 

Michael Wellman

Professor and Associate Chair, Computer Science and Engineering, UM

"Stronger CDA Strategies through Empirical Game-Theoretic Analysis and Reinforcement Learning"

Michael Wellman 1/22 seminar streaming audio file 

Location: 

4-5:30 pm
UM: 1202 SI North, 1075 Beal Ave
WSU: 313 State Hall (via videoconference)

Michael Wellman
Seminar Description: 

L. Julian Schvartzman and Michael P. Wellman

We present a general methodology to automate the search for equilibrium strategies in games derived from computational experimentation. Our approach interleaves empirical game-theoretic analysis with reinforcement learning. We apply this methodology to the classic and widely known Continuous Double Auction game, conducting one of the most comprehensive CDA strategic studies published to date. Empirical game analysis confirms prior findings about the relative performance of known strategies. Reinforcement learning derives new bidding strategies from the empirical equilibrium environment. Iterative application of this approach yields strategies stronger than any other published CDA bidding policy, culminating in a new Nash equilibrium supported exclusively by our learned strategies.

Seminar Speaker Bio: 

Michael Wellman received a PhD from the Massachusetts Institute of Technology in 1988 for his work in qualitative probabilistic reasoning and decision-theoretic planning. From 1988 to 1992, Wellman conducted research in these areas at the USAF's Wright Laboratory. For the past 15+ years, his research has focused on computational market mechanisms for distributed decision making and electronic commerce. As Chief Market Technologist for TradingDynamics, Inc. (now part of Ariba), he designed configurable auction technology for dynamic business-to-business commerce. Wellman previously served as Chair of the ACM Special Interest Group on Electronic Commerce (SIGecom), and as Executive Editor of the Journal of Artificial Intelligence Research. He is a Fellow of the Association for the Advancement of Artificial Intelligence and the Association for Computing Machinery. Also see Michael Wellman's homepage.