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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-v1-8x8
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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-v1-8x8
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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-v1-8x8
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+ type: FrozenLake-v1-8x8
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+ metrics:
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+ - type: mean_reward
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+ value: 0.00 +/- 0.00
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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="Segamboam/q-FrozenLake-v1-8x8", 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 sha256:316e9822c0e51b39cd0eb1130261fd6e6702ac88b33c3396782cea36b447c627
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+ size 2440
replay.mp4 ADDED
Binary file (163 kB). View file
 
results.json ADDED
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+ {"env_id": "FrozenLake-v1", "mean_reward": 0.0, "n_eval_episodes": 150, "eval_datetime": "2022-12-27T21:19:01.377992"}