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Poker Hand
Straight Flush

Just when the poker craze was hitting its peak in early of 2005, I decided to take it upon myself to develop an AI capable of competing and winning at the most popular game of poker at the time: Texas Hold’Em. A daunting task - though, those are the ones which are most fun. :)

After doing a fair amount research, I stumbled across the University of Alberta Gaming Group. This group had created two Hold’Em-playing bots which they referred to as Poki & PsOpti. The development of PsOpti really interested me, as it was based on the principles of Game Theory, whereas Poki was based on what seemed like intelligent guesswork.

I have since created an advanced game-theoretic algorithm capable of beating PsOpti in 2-Player Heads-Up Hold’Em. The general approach used to create my player can be described simply as a combination of appropriate abstraction techniques and player training using the principles of Fictitious Play.

My work for this project has been accepted to the 2006 Conference on Artificial Intelligence where I will present the paper which is linked to at the bottom of this page.

If you have any questions, please feel free to send me an email.


Project started in January 2005. Current version is 4.0 written in VB.NET & C++.


Published in the proceedings of the 2006 Conference on Artificial Intelligence:

Download the paper in Adobe PDF format:
Using Fictitious Play to Find Pseudo-Optimal Solutions for Full-Scale Poker