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