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 gym
from stable_baselines3 import PPO
from huggingface_sb3 import load_from_hub

checkpoint = load_from_hub(
	repo_id="dmenini/ppo-LunarLander-v2",
	filename="ppo-LunarLander-v2.zip"
)

model = PPO.load(checkpoint)

env = gym.make("LunarLander-v2")

# Evaluate the agent and watch it
eval_env = gym.make("LunarLander-v2")
mean_reward, std_reward = evaluate_policy(
    model, eval_env, render=True, n_eval_episodes=5, deterministic=True, warn=False
)
print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")