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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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+
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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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