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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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## 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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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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## Results
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[INFO] Pyramids. Step: 2320000. Time Elapsed: 4995.783 s. Mean Reward: 1.775. Std of Reward: 0.113.
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## Hyperparameters
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```yaml
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%%file /content/ml-agents/config/ppo/PyramidsRND.yaml
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behaviors:
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Pyramids:
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trainer_type: ppo
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hyperparameters:
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batch_size: 252
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buffer_size: 4096
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learning_rate: 0.0003
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beta: 0.01
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epsilon: 0.2
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lambd: 0.95
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num_epoch: 3
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learning_rate_schedule: linear
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network_settings:
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normalize: false
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hidden_units: 512
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num_layers: 2
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vis_encode_type: nature_cnn
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reward_signals:
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extrinsic:
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gamma: 0.99
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strength: 1.0
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rnd:
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gamma: 0.99
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strength: 0.01
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network_settings:
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hidden_units: 64
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num_layers: 3
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learning_rate: 0.0001
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keep_checkpoints: 5
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max_steps: 3000000
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time_horizon: 512
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summary_freq: 10000
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```
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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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