README.md

metadata

library_name: ml-agents
tags:
  - Pyramids
  - deep-reinforcement-learning
  - reinforcement-learning
  - ML-Agents-Pyramids
  - PPO
  - Unity
model-index:
  - name: PPO-PyramidsTraining6
    results:
      - task:
          type: reinforcement-learning
          name: reinforcement-learning
        dataset:
          name: Pyramids
          type: Unity-MLAgents-Env
        metrics:
          - type: mean_reward
            value: 1.381
            name: mean_reward
            verified: false
          - type: std_reward
            value: 0
            name: std_reward
            verified: false

ppo Agent playing Pyramids

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

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: KraTUZen/ppo-PyramidsTraining
3. Step 2: Select your .nn /.onnx file
4. Click on Watch the agent play 👀