Raising the Stakes

Jonathan Schaeffer, Department of Computing Science, University of Alberta, Canada

Poker is a challenging problem for artificial intelligence research: multiple opponents (up to 10), stochastic element (cards being dealt), imperfect information (don't know the opponent's cards), deception (bluffing), user modeling (identifying player patterns), and risk management (betting decisions). Unlike the classic A1 game, chess, poker is more relevant to real-world situations including negotiations, military strategy, and e-commerce.

For over ten years, the University of Alberta Computer Poker Group has been working on building a high-performance poker program. This work has led us through four distinct phases of program design:

1. knowledge-based system,
2. simulations,
3. game theory, and
4. tree searching with learning.

The prospects of a program successfully challenging the best human players in the near future is excellent. In this talk we will motivate the research, compare the different program designs, and discuss future directions.

The P/T Colloquium is
typically held each
Thursday, 3:45–5:00 PM.
Refreshments are served
at 3:15 PM.