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---
tags:
- FrozenLake-v1-4x4
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4
type: FrozenLake-v1-4x4
metrics:
- type: mean_reward
value: 0.74 +/- 0.44
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Codes
Github repos(Give a star if found useful):
* https://github.com/hishamcse/DRL-Renegades-Game-Bots
* https://github.com/hishamcse/Advanced-DRL-Renegades-Game-Bots
* https://github.com/hishamcse/Robo-Chess
Kaggle Notebook:
* https://www.kaggle.com/code/syedjarullahhisham/drl-huggingface-unit-2-frozenlake-v1-taxi-v3
## Usage
```python
model = load_from_hub(repo_id="hishamcse/q-FrozenLake-v1-4x4", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
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