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  1. README.md +35 -0
  2. q-learning.pkl +3 -0
  3. replay.mp4 +0 -0
  4. results.json +1 -0
README.md ADDED
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+ ---
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+ tags:
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+ - FrozenLake-v1-4x4
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+ - q-learning
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+ - reinforcement-learning
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+ - custom-implementation
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+ model-index:
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+ - name: q-FrozenLake-v1-4x4-Slippery
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+ results:
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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: FrozenLake-v1-4x4
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+ type: FrozenLake-v1-4x4
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+ metrics:
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+ - type: mean_reward
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+ value: 0.27 +/- 0.44
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+ name: mean_reward
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+ verified: false
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+ ---
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+
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+ # **Q-Learning** Agent playing1 **FrozenLake-v1**
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+ This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
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+
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+ ## Usage
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+
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+ ```python
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+
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+ model = load_from_hub(repo_id="mitro99/q-FrozenLake-v1-4x4-Slippery", filename="q-learning.pkl")
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+
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+ # Don't forget to check if you need to add additional attributes (is_slippery=False etc)
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+ env = gym.make(model["env_id"])
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+ ```
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+
q-learning.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:666cb6403d389f510ea47f9f97e775b5be9321b3677be4ce12e0c63c0300f845
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+ size 904
replay.mp4 ADDED
Binary file (43.7 kB). View file
 
results.json ADDED
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+ {"env_id": "FrozenLake-v1", "mean_reward": 0.27, "n_eval_episodes": 100, "eval_datetime": "2022-12-27T12:44:18.737096"}