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ash-171/
ppo-LunarLander-v3

Name: ppo-LunarLander-v3
Availability: InStock

stable-baselines3

LunarLander-v3

deep-reinforcement-learning

reinforcement-learning

model-index

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PPO Agent playing LunarLander-v3

This is a trained model of a PPO agent playing LunarLander-v3 using the stable-baselines3 library.

Usage (with Stable-baselines3)

python

import gymnasium as gym

from huggingface_sb3 import load_from_hub
from stable_baselines3 import PPO
from stable_baselines3.common.evaluation import evaluate_policy

# Retrieve the model from the hub
checkpoint = load_from_hub(
    repo_id="ash-171/ppo-LunarLander-v3",
    filename="ppo-LunarLander-v3.zip",
)
model = PPO.load(checkpoint)

# Evaluate the agent and watch it
eval_env = gym.make("LunarLander-v3")
mean_reward, std_reward = evaluate_policy(
    model, eval_env, render=False, n_eval_episodes=10, deterministic=True, warn=False
)
print(f"mean_reward={mean_reward:.2f} +/- {std_reward}").