FrozenLake-v1-4x4-no_slippery q-learning reinforcement-learning custom-implementation model-index region:us
---
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 playing **FrozenLake-v1**

This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .

## Usage

```python
model = load_from_hub(repo_id = "crossroderick/q-FrozenLake-v1-4x4-noSlippery", filename = "q-learning.pkl")
```

This particular model was trained on the default version of FrozenLake-v1 in a 4x4 setting, so don't forget to set `is_slippery = False` and 
specify `map_name` when loading the environment, such as:

```python
env = gym.make(model["env_id"], map_name = "4x4", is_slippery = False)
```
