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---
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library_name: ml-agents
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tags:
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- Pyramids
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- deep-reinforcement-learning
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- reinforcement-learning
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- ML-Agents-Pyramids
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- curiosity
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- RND
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---
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# **ppo** Agent playing **Pyramids**
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This is a trained model of a **ppo** agent playing **Pyramids**
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using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
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This agent uses **Random Network Distillation (RND)** for curiosity-driven exploration to solve the Pyramids environment, where it must press a button to spawn a pyramid, navigate to it, knock it over, and reach the gold brick at the top.
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## Usage (with ML-Agents)
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The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
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We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
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- A *short tutorial* where you teach Huggy the Dog to fetch the stick and then play with him directly in your
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browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
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- A *longer tutorial* to understand how works ML-Agents:
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https://huggingface.co/learn/deep-rl-course/unit5/introduction
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### Resume the training
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```bash
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mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume |
