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---
tags:
- CartPole-v1
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Q-Cartpole-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_reward
value: 94.79 +/- 12.53
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing **CartPole-v1**
This is a trained model of a **Q-Learning** agent playing **CartPole-v1** .
## Usage
```python
model = load_from_hub(repo_id="artbreguez/Q-Cartpole-v1", filename="q-learning.pkl")
env = gym.make(model["env_id"])
evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"])
```
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