Commit
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Parent(s):
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Push Q-Learning agent to Hub
Browse files- .gitattributes +1 -0
- README.md +35 -0
- q-learning.pkl +3 -0
- replay.mp4 +3 -0
- results.json +1 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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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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tags:
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- FrozenLake-v1-4x4-no_slippery
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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-noSlippery
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results:
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- metrics:
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- type: mean_reward
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value: 1.00 +/- 0.00
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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: FrozenLake-v1-4x4-no_slippery
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type: FrozenLake-v1-4x4-no_slippery
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---
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# **Q-Learning** Agent playing **FrozenLake-v1**
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This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
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## Usage
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```python
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model = load_from_hub(repo_id="dvalbuena1/q-FrozenLake-v1-4x4-noSlippery", 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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evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"])
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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 sha256:9e98a2445193951bbe55c4d271cd3af3deb7f204d9f8899f7872794548ec2640
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size 914
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replay.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:56ba66361f81e2d1dc4305e8bf921c20f263b0bc4d100906461f7c0c85364958
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size 31943
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results.json
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{"env_id": "FrozenLake-v1", "mean_reward": 1.0, "n_eval_episodes": 100, "eval_datetime": "2022-08-19T21:38:43.027906"}
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