First pass of DQN
Browse files- .gitattributes +1 -0
- README.md +28 -0
- config.json +1 -0
- dqn-LunarLander-v2.zip +3 -0
- dqn-LunarLander-v2/_stable_baselines3_version +1 -0
- dqn-LunarLander-v2/data +120 -0
- dqn-LunarLander-v2/policy.optimizer.pth +3 -0
- dqn-LunarLander-v2/policy.pth +3 -0
- dqn-LunarLander-v2/pytorch_variables.pth +3 -0
- dqn-LunarLander-v2/system_info.txt +7 -0
- replay.mp4 +3 -0
- results.json +1 -0
.gitattributes
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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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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- LunarLander-v2
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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: DQN
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results:
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- metrics:
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- type: mean_reward
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value: 134.84 +/- 126.67
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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: LunarLander-v2
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type: LunarLander-v2
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---
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# **DQN** Agent playing **LunarLander-v2**
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This is a trained model of a **DQN** agent playing **LunarLander-v2** 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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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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{"mean_reward": 134.84259101537123, "std_reward": 126.67250248052723, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-05T18:05:11.431634"}
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