README.md

metadata

tags:
  - FrozenLake-v1-4x4-no_slippery
  - q-learning
  - reinforcement-learning
  - custom-implementation
  - gymnasium
model-index:
  - name: q-frozen-lake-v1-4x4-no-slippery
    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 to the Gymnasium FrozenLake-v1 reinforcement learning environment.

Usage

model = load_from_hub(repo_id="coding-kelps/q-frozen-lake-v1-4x4-no-slippery", 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"])

References

You can find the original source code of the model training in the corresponding Coding Kelps aquaqym repository.