kenhatt/ppo-Lunar-Lander-v2

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 ...
from huggingface_sb3 import load_from_hub

model = PPO(
    policy= 'MlpPolicy', 
    env = env,
    n_steps=2048,
    batch_size = 16,
    verbose=1)

model.learn(total_timesteps=1000000)

model_name = "callmekenta-ppo-LunarLander-v2"
model.save(model_name)

eval_env = Monitor(gym.make("LunarLander-v2", render_mode='rgb_array'))

mean_reward, std_reward = evaluate_policy(model,eval_env, n_eval_episodes=10, deterministic=True)

print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")
...