As a game of incomplete information and uncertainty, poker is a prime application of the game theory concepts and decision making skills essential to trading. While traders make risk decisions based on the limited information they get from the markets, poker players make decisions based on hidden information as well, taking into account factors such as expected value and probability distributions.
It is! To build a working pokerbot only requires both critical thinking ability and an eagerness to learn. However, an understanding of machine learning, algorithms, and data science can go a long way towards creating an advanced pokerbot. Competitiors can code in whatever language they want, but we offer support in C++, Python, and Java.
We welcome students with all levels of programming experience. Nevertheless, some previous coding experience would certainly be helpful. Although not necessary, we recommend you have at least one team member with some programming experience.
We are keeping the game and tournament structure secret. You will hear all about it during the challenge unveiling in early January 2020.
Teams may be composed of 1-4 players.
You will need to submit functioning pokerbots for various checkpoints throughout the course, as well as a short strategy report at the end of IAP.
For our course and tournament in January, you must be able to register for MIT IAP classes. If you are cross-registering, bring your papers in on the first day of class for us to sign.
IAP pre-registration will open in December!
Creating a functioning pokerbot takes no time at all. However, creating a competitive and strategic pokerbot will require more effort and experimentation. Ultimately, the more you put into your pokerbot, the more value you will receive from the class!