README.md

metadata

library_name: stable-baselines3
tags:
  - LunarLander-v2
  - deep-reinforcement-learning
  - reinforcement-learning
  - stable-baselines3
model-index:
  - name: PPO
    results:
      - metrics:
          - type: mean_reward
            value: 276.26 +/- 18.75
            name: mean_reward
        task:
          type: reinforcement-learning
          name: reinforcement-learning
        dataset:
          name: LunarLander-v2
          type: LunarLander-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)

model = PPO( policy = 'MlpPolicy', env = env, n_steps = 1024, batch_size = 32, n_epochs = 4, gamma = 0.9990, gae_lambda = 0.995, ent_coef = 0.005, verbose=1)

model.learn(total_timesteps=2000000)