Computer Science Department Seminar: AI Techniques for Computing Game-Theoretic Solutions
Vincent Conitzer
Carnegie Mellon University
School of Computer Science
Computer Science Department Seminar
Faculty Host:Shlomo Zilberstein
"AI Techniques for Computing Game-Theoretic Solutions"
Computer scientists are increasingly confronted with settings where multiple self-interested parties (humans or software agents) interact, especially in the context of the Internet. Examples include auctions, exchanges, elections, and other negotiation protocols; as well as job scheduling, routing, and webpage ranking. In these settings, the best action for one agent to take generally depends on what the other agents do, so that it is not immediately clear what "acting optimally" means. Game theory provides various notions of how agents should act in such domains. However, these concepts become useful only when we can compute the solutions that they prescribe, and this leads to nontrivial AI problems.
In this talk, I will first review some basic solution concepts from game theory, including dominance and Nash equilibrium. Then I will present our recent work on computing solutions according to these concepts as well as another new concept that we introduced. I will also briefly discuss my work on other topics, such as the design of the mechanisms within which the agents interact.
Vincent Conitzer is a Ph.D. student at Carnegie Mellon University, advised by Tuomas Sandholm (a UMass Amherst Ph.D. alum). He holds an M.S. in Computer Science from CMU (2003) and a B.A. in Applied Mathematics from Harvard (2001). He has published over 30 papers on computational issues in game theory, mechanism design, auctions, elections, and other negotiation settings. He is supported by an IBM Ph.D. Fellowship.
Refreshments at 3:45 PM in the atrium, outside the presentation room.
Please visit our departmental calendar at http://macdb.cs.umass.edu/cal/
for information on upcoming events.
