In this project, we design an intelligent agent to play Limit Texas Hold’Em Poker. We propose a novel adaptive agent designed to predict an accurate representation of its hand strength, through Monte Carlo simulations, and to extract information about the opponent’s behaviour and hand strength through opponent mapping. The agent utilises a nested evaluation function to determine its actions through Bayesian Inference, adapting its strategy based on the opponent.
The "example.py" file can be used to run a simulation of the two-player game.
Our poker agent can be found in the Group26Player.py file. The agent can be called using "from Group26Player import Group26Player".
Please do take a look at "Poker Project - Team 26.pdf" for our full technical report!
The PyPokerEngine is adapted from link