README.md

metadata

tags:
  - deep-reinforcement-learning
  - reinforcement-learning
  - stable-baselines3
  - LunarLander-v2
model-index:
  - name: PPO
    results:
      - task:
          type: reinforcement-learning
          name: LunarLander-v2
        dataset:
          name: LunarLander-v2
          type: LunarLander-v2
        metrics:
          - type: mean_reward
            value: 273 +/- 9.50
            name: mean_reward

PPO Agent for LunarLander-v3 (Optimized)

This is a pre-trained model for LunarLander-v3 using Stable-Baselines3.

Usage

import gymnasium as gym
from stable_baselines3 import PPO
from stable_baselines3.common.env_util import make_vec_env
from stable_baselines3.common.vec_env import VecNormalize

# Load the environment
env = make_vec_env("LunarLander-v3", n_envs=1)
env = VecNormalize.load("vec_normalize.pkl", env)
env.training = False
env.norm_reward = False

# Load the model
model = PPO.load("ppo_lunar_optimized", env=env)