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)
import gymnasium as gym
from stable_baselines3 import PPO
from stable_baselines3.common.evaluation import evaluate_policy
from stable_baselines3.common.monitor import Monitor
model = PPO.load("ppo-LunarLander-v2")
eval_env = Monitor(gym.make("LunarLander-v2"))
mean_reward, std_reward = evaluate_policy(model, eval_env)
print(f"Mean reward={mean_reward} +- {std_reward}")
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Evaluation results
- mean_reward on LunarLander-v2self-reported297.29 +/- 10.10