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Pool Agent Reinforcement Learning

Gymnasium environment for 8-ball pool, using FastFiz to simulate the physics of the game.

Preqrequisites

The package, python3-opengl is required to run the environment. Install it using the following command:

apt-get install python3-opengl

Installation

Install the package using the following command:

pip install .

Usage

Use the environment for training a reinforcement learning agent:

from stable_baselines3 import PPO
from fastfiz_env import DefaultReward, make

env = make("FastFiz-v0", reward_function=DefaultReward, num_balls=2)

model = PPO("MlpPolicy", env)

model.learn(total_timesteps=100_000)

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