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)```
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Evaluation results
- mean_reward on LunarLander-v2self-reported286.34 +/- 10.43