This project is a Texas Hold’em poker game developed based on personal interest. I built the game framework using Python and created computer players using rule-based methods. This game supports up to 9 players. Currently, the most interesting part is the 1v1 game, which allows for comparing different AI strategies and enables human players to compete against AI. The ultimate goal is to implement AI players using genuine artificial intelligence techniques, but this would require further study and learning to design and implement.
While the current computer strategy is purely rule-based, it is not entirely naive. Avoid attempting overly aggressive bluffing strategies, as it will likely result in significant losses. The game is fair. The computer don’t know your hand cards.
The game’s graphical interface displays your hand cards and the community cards, but all interactions occur within the Terminal. When it’s your turn to make a move, you’ll have access to the entire history of the current game.
You are very welcomed to click the Code link to github, and deploy on your own computer to play. Also please checkout the Video for your reference.
Liyang Wang
Senior Supervisor R&D Engineer
My research interests include robotics, reinforcement learning, deep learning, path planning, motion planning, trajectory optimization, and controller design.