 
# **Q-Learning** Agent playing1 **Taxi-v3** 
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** . 
## Usage 
```python 
model = load_from_hub(repo_id="YCHuang2112/q-Taxi-v3", 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"]) 

{"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/- 2.71", "name": "mean_reward", "verified": false}]}]}]}
Taxi-v3 q-learning reinforcement-learning custom-implementation model-index region:us
TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us 

 
# Q-Learning Agent playing1 Taxi-v3 
This is a trained model of a Q-Learning agent playing Taxi-v3 . 
## Usage 
'''python 
model = load_from_hub(repo_id="YCHuang2112/q-Taxi-v3", filename="URL") 
# Don't forget to check if you need to add additional attributes (is_slippery=False etc) 
env = URL(model["env_id"]) 

# Q-Learning Agent playing1 Taxi-v3 
This is a trained model of a Q-Learning agent playing Taxi-v3 . ## Usage 
'''python 
model = load_from_hub(repo_id="YCHuang2112/q-Taxi-v3", filename="URL") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) 
env = URL(model["env_id"])
TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us 
 # Q-Learning Agent playing1 Taxi-v3 
This is a trained model of a Q-Learning agent playing Taxi-v3 . ## Usage 
'''python 
model = load_from_hub(repo_id="YCHuang2112/q-Taxi-v3", filename="URL") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) 
env = URL(model["env_id"])