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: 286.34 +/- 10.43
            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)

  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)```