sjin59/poca-SoccerTwos

poca Agent playing SoccerTwos

This is a trained model of a poca agent playing SoccerTwos using the Unity ML-Agents Library.

Training details

• Trainer: POCA (with self-play)
• Steps: 5,000,000
• Final ELO: ~1579 (peak: 1615)
• Hardware: CPU

Usage (with ML-Agents)

The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/

We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:

• A short tutorial where you teach Huggy the Dog to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
• A longer tutorial to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction

Resume the training

mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume

Watch your Agent play

You can watch your agent playing directly in your browser

1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
2. Step 1: Find your model_id: sjin59/poca-SoccerTwos
3. Step 2: Select your .nn /.onnx file
4. Click on Watch the agent play