---
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"])
```