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enrique2701
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ppo-Pyramids

Reinforcement Learning
ml-agents
TensorBoard
ONNX
Pyramids
deep-reinforcement-learning
ML-Agents-Pyramids
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ppo-Pyramids
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---
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 👀