| | --- |
| | library_name: ml-agents |
| | tags: |
| | - Pyramids |
| | - deep-reinforcement-learning |
| | - reinforcement-learning |
| | - ML-Agents-Pyramids |
| | --- |
| | |
| | # **ppo** Agent playing **Pyramids** |
| | This is a trained model of a **ppo** agent playing **Pyramids** |
| | using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). |
| |
|
| | ## Results |
| | [INFO] Pyramids. Step: 2320000. Time Elapsed: 4995.783 s. Mean Reward: 1.775. Std of Reward: 0.113. |
| |
|
| | ## Hyperparameters |
| | ```yaml |
| | %%file /content/ml-agents/config/ppo/PyramidsRND.yaml |
| | behaviors: |
| | Pyramids: |
| | trainer_type: ppo |
| | hyperparameters: |
| | batch_size: 252 |
| | buffer_size: 4096 |
| | learning_rate: 0.0003 |
| | beta: 0.01 |
| | epsilon: 0.2 |
| | lambd: 0.95 |
| | num_epoch: 3 |
| | learning_rate_schedule: linear |
| | network_settings: |
| | normalize: false |
| | hidden_units: 512 |
| | num_layers: 2 |
| | vis_encode_type: nature_cnn |
| | reward_signals: |
| | extrinsic: |
| | gamma: 0.99 |
| | strength: 1.0 |
| | rnd: |
| | gamma: 0.99 |
| | strength: 0.01 |
| | network_settings: |
| | hidden_units: 64 |
| | num_layers: 3 |
| | learning_rate: 0.0001 |
| | keep_checkpoints: 5 |
| | max_steps: 3000000 |
| | time_horizon: 512 |
| | summary_freq: 10000 |
| | ``` |
| | ## 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 |
| | ```bash |
| | 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: enrique2701/ppo-Pyramids |
| | 3. Step 2: Select your *.nn /*.onnx file |
| | 4. Click on Watch the agent play 👀 |
| | |
