PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
Usage (with Stable-baselines3)
from stable_baselines3 import PPO
from stable_baselines3.common.monitor import Monitor
from huggingface_sb3 import load_from_hub
repo_id = "helamri/PPO-LunarLander-v2"
filename = "PPO-LunarLander-v2.zip"
checkpoint = load_from_hub(repo_id, filename)
model = PPO.load(checkpoint, print_system_info=True)
eval_env = Monitor(gym.make("LunarLander-v2", render_mode="human"))
mean_rwd, std_rwd = evaluate_policy(model, eval_env, n_eval_episodes=10)
print(f"mean_reward: {mean_rwd}±{std_rwd}")
- Downloads last month
- 0
Evaluation results
- mean_reward on LunarLander-v2self-reported244.16 +/- 18.09