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Texas Hold'em CFR

This repository explores Texas Hold'em solvers using a custom build of Counter Factual Regret Minimization (CFR) written in Cython for Macbook Pro M1.

• Note: The code is poorly written and maintained.
• Note: The code is not optimized for interpretability.

Features

• Blueprint Training: Solve positions iteratively to build a solution index.
• Counter Factual Regret Minimization (CFR).
• Action space traversal and lookups (cfr.fast_forward_gamestate).
• Self/Human-play in Retro Style (poker_game.play_game).

Planned Enhancements

• Implement postflop abstractions. (Done, but is based on lossy heuristics)
• Optimize and debug CFR functionalities.
• Log hands for analysis on GTO Wizard.
• Improve GameState and betting history management.
• Refine preflop blueprint construction.
• Refine postflop blueprint construction.
• Build an interactive API for playing/testing.

Example

The following is a range chart that displays how often the (UTG) should open raise 1.5x the pot (1.5bb * 1.5 = 2.25bb) in 6-Max Texas Hold'em. Iterations search depth and gamestate hashing are restricted due to memory limitations and performance constraints. The sampled range reflects a loose version of what might be seen on GTO Wizard.

Installation

To install and run the project, follow these steps:

1. Install Anaconda Package Manager for Python.

2. Create the Anaconda Environment:

   conda create --name serene python=3.8.8 numpy pandas cython scikit-learn tqdm matplotlib psutil

3. Activate the Anaconda Environment:

   conda activate serene

4. Clone and navigate to the source folder:

   git clone https://github.com/guy477/serene.git
   cd serene/src

5. Compile the project:

   python setup.py build_ext --inplace

6. Run the current implementation:

   python main.py

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