Abstract:

Poker provides an excellent testbed for studying decision-making under conditions of uncertainty. There are many benefits to be gained from designing and experimenting with poker programs. It is a game of imperfect knowledge, where multiple competing agents must understand estimation, prediction, risk management, deception, counter-deception, and agent modeling. New evaluation techniques for estimating the strength and potential of a poker hand are presented. This thesis describes the implementation of a program that successfully handles all aspects of the game, and uses adaptive opponent modeling to improve performance.

Acknowledgements