README.md

metadata

tags:
  - FrozenLake-v1-8x8
  - q-learning
  - reinforcement-learning
  - custom-implementation
model-index:
  - name: q-FrozenLake-v1-8x8
    results:
      - task:
          type: reinforcement-learning
          name: reinforcement-learning
        dataset:
          name: FrozenLake-v1-8x8
          type: FrozenLake-v1-8x8
        metrics:
          - type: mean_reward
            value: 0.17 +/- 0.38
            name: mean_reward
            verified: false

Q-Learning Agent playing1 FrozenLake-v1

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

Codes

Github repos(Give a star if found useful):

• https://github.com/hishamcse/DRL-Renegades-Game-Bots
• https://github.com/hishamcse/Advanced-DRL-Renegades-Game-Bots
• https://github.com/hishamcse/Robo-Chess

Kaggle Notebook:

• https://www.kaggle.com/code/syedjarullahhisham/drl-huggingface-unit-2-frozenlake-v1-taxi-v3

Usage

model = load_from_hub(repo_id="hishamcse/q-FrozenLake-v1-8x8", 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"])