A collection of Reinforcement Learning algorithms to train autonomous agents in different environments.
Project description
EnvQuest
Play with reinforcement learning algorithms.
Requirements
You need these requirements to run the project:
- python >= 3.8
- uv
- ffmpeg
# Linux
sudo apt install ffmpeg
# MacOS
brew install ffmpeg
Installation
Install the python dependencies
uv venv .venv
source .venv/bin/activate
uv sync --frozen
Start a local WandB server to track your experiments
wandb server start
Usage
Run a random policy agent
Run a random agent in a Gym environment
python -m scripts.run_random_agent
Read the python script for more information: scripts/run_random_agent.py
Train Agents
DQN Agent
Train a DQN policy agent in a Gym environment
python -m scripts.train_dqn
Read the python script for more information: scripts/train_dqn.py
Sarsa Agent
Train a Sarsa policy agent in a Gym environment
python -m scripts.train_sarsa
Read the python script for more information: scripts/train_sarsa.py
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