Welcome to AutoRL X 👋

Interactive Platform for Automated Reinforcement Learning on the Web

With Auto RL X you can interactively create reinforcement learning gyms, execute optimization runs and visually inspect agent performance directly in your browser. 🖥 📊 🤖

AutoRL X is provided under GPL 3.0 license.

The code base further depends on:

• https://github.com/lorifranke/arlo.git (a fork of https://github.com/arlo-lib/ARLO)
• https://github.com/lorifranke/mushroom-rl.git (a fork of https://github.com/MushroomRL/mushroom-rl)

Installation

This will deploy a MySQL database, AutoRL X Server and the AutoRL X web interface in your local Docker environment using Docker Compose.

Prerequisites 🐳

Install Docker from https://www.docker.com/.

🟢 Deploy

From your terminal, to pull and deploy prebuilt images, execute

sh deploy_by_pull.sh    # Deploys prebuilt images and starts the composition

Alternatively, to build and deploy images locally, execute

sh deploy_by_build.sh   # Builds locally, deploys and starts the composition

Don't hesitate to open an issue if you need help.

🟡 Restart

After deployment, to stop and restart the composition, execute

sh stop.sh              # Stops the composition
sh start.sh             # Starts the compositions

🔴 Undeploy

From your terminal, execute

sh undeploy.sh          # Stops and undeploys the composition

Developers

Run AutoRL X Server w/ Python:

cd server
pip install .           # Installs dependencies
python main.py &        # Listens to port 8000

Run AutoRL X w/ NPM:

cd ..
npm install             # Installs dependencies
npm run dev &           # Listens to port 5173

How to cite us:

@article{franke2023autorl,
  title={AutoRL X: Automated Reinforcement Learning on the Web},
  author={Franke, Loraine and Weidele, Daniel Karl I and Dehmamy, Nima and Ning, Lipeng and Haehn, Daniel},
  journal={ACM Transactions on Interactive Intelligent Systems},
  year={2023},
  publisher={ACM New York, NY}
}