readme: ---
  tags:
  - Taxi-v3
  - q-learning
  - reinforcement-learning
  - custom-implementation
  model-index:
  - name: q-Taxi-v3
    results:
    - metrics:
      - type: mean_reward
        value: 7.56 +/- 2.71
        name: mean_reward
      task:
        type: reinforcement-learning
        name: reinforcement-learning
      dataset:
        name: Taxi-v3
        type: Taxi-v3
  ---
  
    # **Q-Learning** Agent playing **Taxi-v3**
    This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
    
    ## Usage
    ```python
    model = load_from_hub(repo_id="dmitry-np/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"])
  
    evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"])
    
    ```
    