README.md

metadata

tags:
  - CartPole-v1
  - reinforce
  - reinforcement-learning
  - custom-implementation
  - deep-rl-class
model-index:
  - name: Reinforce-CartPole-v1
    results:
      - task:
          type: reinforcement-learning
          name: reinforcement-learning
        dataset:
          name: CartPole-v1
          type: CartPole-v1
        metrics:
          - type: mean_reward
            value: 31.55 +/- 14.99
            name: mean_reward
            verified: false

Q-Learning Agent playing CartPole-v1

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

Usage

model = load_from_hub(repo_id="sayby/Reinforce-CartPole-v1", 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"])

 
      ```