readme: ---
  tags:
  - FrozenLake-v1-4x4-no_slippery
  - q-learning
  - reinforcement-learning
  - custom-implementation
  model-index:
  - name: q-FrozenLake-v1-4x4-noSlippery
    results:
    - task:
        type: reinforcement-learning
        name: reinforcement-learning
      dataset:
        name: FrozenLake-v1-4x4-no_slippery
        type: FrozenLake-v1-4x4-no_slippery
      metrics:
      - type: mean_reward
        value: 1.00 +/- 0.00
        name: mean_reward
        verified: false
  ---
  
    # **Q-Learning** Agent playing1 **FrozenLake-v1**
    This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
  
    ## Usage
  
    ```python
    
    model = load_from_hub(repo_id="rematchka/q-FrozenLake-v1-4x4-noSlippery", 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"])
    ```
    