Upload PPO MountainCar-v0 trained agent
Browse files- .gitattributes +1 -0
- MountainCar-v0.zip +3 -0
- MountainCar-v0/_stable_baselines3_version +1 -0
- MountainCar-v0/data +74 -0
- MountainCar-v0/policy.optimizer.pth +3 -0
- MountainCar-v0/policy.pth +3 -0
- MountainCar-v0/pytorch_variables.pth +3 -0
- MountainCar-v0/system_info.txt +7 -0
- README.md +28 -0
- config.json +1 -0
- replay.mp4 +3 -0
- results.json +1 -0
.gitattributes
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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MountainCar-v0.zip
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MountainCar-v0/data
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"normalize_advantage": true,
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}
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MountainCar-v0/policy.optimizer.pth
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version https://git-lfs.github.com/spec/v1
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size 623
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MountainCar-v0/policy.pth
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version https://git-lfs.github.com/spec/v1
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size 39873
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MountainCar-v0/pytorch_variables.pth
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version https://git-lfs.github.com/spec/v1
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size 431
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MountainCar-v0/system_info.txt
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OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
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Python: 3.7.13
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Stable-Baselines3: 1.5.0
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PyTorch: 1.11.0+cu113
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GPU Enabled: True
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Numpy: 1.21.6
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Gym: 0.21.0
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README.md
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---
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library_name: stable-baselines3
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tags:
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- MountainCar-v0
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- deep-reinforcement-learning
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- reinforcement-learning
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- stable-baselines3
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model-index:
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- name: PPO
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results:
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- metrics:
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- type: mean_reward
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value: -115.60 +/- 2.87
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name: mean_reward
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task:
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name: MountainCar-v0
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type: MountainCar-v0
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---
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# **PPO** Agent playing **MountainCar-v0**
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This is a trained model of a **PPO** agent playing **MountainCar-v0** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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## Usage (with Stable-baselines3)
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TODO: Add your code
|
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config.json
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replay.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:25f6c81ca9909eb27c72b4ecd38929761e62f6eef93a6ed6bc820a2a76ebaab1
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size 245399
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results.json
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{"mean_reward": -115.6, "std_reward": 2.870540018881465, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-12T12:38:26.491006"}
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