Q-Learning Agent playing CartPole-v1
This is a trained model of a Reinforce agent playing CartPole-v1 .
Usage
model = load_from_hub(repo_id="sayby/Reinforce-CartPole-v1", filename="model.pt")
# 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["eval_seed"])
Evaluation results
- mean_reward on CartPole-v1self-reported109.92 +/- 16.87