11/1/2001
3:30pm-4:30pm
ECCR 265
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Electronic Commerce, Auctions, and Computational Game Theory: Some Results that Exploit Computational and Representational Restrictions on the Behavior of Agents
Syntek Capital
Multi-agent games are becoming an increasingly prevalent formalism for the study
of electronic commerce and auctions. In order to act efficiently in such complex
settings agents will adopt both representational and computational restrictions
on their behavior (much as in the rest of artificial intelligence and machine
learning). Computational game theory studies the impact of such restrictions on
the outcome of games.
In this talk, I will present some of my recent work with colleagues at AT&T
Labs in this area beginning with a motivating description of a trading-agent
competition in which we participated. Following that, I will present a result
that analyzes the behavior of agents that incrementally adapt their strategy
through gradient ascent on expected payoff, in the simple setting of two-player,
two-action, iterated general-sum games. I will show that surprisingly either the
agents will converge to a Nash equilibrium, or if the strategies themselves do
not converge, then their average payoffs will nevertheless converge to the
payoffs of a Nash equilibrium. Finally, I will introduce a compact
graph-theoretic representation for multi-party game theory and provide a
provably correct and efficient algorithm for computing approximate Nash
equilibria in (one-stage) games represented by trees or sparse graphs.
Hosted by Michael Mozer.
Refreshments will be served immediately following the talk in ECOT 831.
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