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Browse files- README.md +35 -0
- q-learning.pkl +3 -0
- replay.mp4 +0 -0
- results.json +1 -0
README.md
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---
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tags:
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- Taxi-v3
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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: Taxi-v3-Q-learning
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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: Taxi-v3
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type: Taxi-v3
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metrics:
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- type: mean_reward
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value: 7.46 +/- 2.78
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name: mean_reward
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verified: false
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---
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# **Q-Learning** Agent playing1 **Taxi-v3**
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This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
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## Usage
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```python
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model = load_from_hub(repo_id="malamasn/Taxi-v3-Q-learning", filename="q-learning.pkl")
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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
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version https://git-lfs.github.com/spec/v1
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oid sha256:4a17fc2a1cf6082cd14dc5df167beed550f58e885a367c13c4963960913eb1e4
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size 24570
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replay.mp4
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Binary file (111 kB). View file
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results.json
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{"env_id": "Taxi-v3", "mean_reward": 7.46, "n_eval_episodes": 100, "eval_datetime": "2023-01-04T12:04:39.616568"}
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