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---
tags:
- FrozenLake-v1-8x8
- q-learning
- reinforcement-learning
- custom-implementation
- SL-Sprout
model-index:
- name: q-FrozenLake-v1-8x8
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-8x8
type: FrozenLake-v1-8x8
metrics:
- type: mean_reward
value: 0.69 +/- 0.46
name: mean_reward
verified: false
---
# sl_Sprout **Q-Learning** Agent playing **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1**.
## Usage
```python
model = load_from_hub(repo_id="AllIllusion/q-FrozenLake-v1-8x8", filename="sl_TabularModel_FrozenLake-v1.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["FrozenLake-v1"])
```
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