PPO Agent Playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 coded from scratch with CleanRL architecture.
Hyperparameters
{'exp_name': 'ppo',
'seed': 1,
'torch_deterministic': True,
'cuda': True,
'track': False,
'wandb_project_name': 'cleanRL',
'wandb_entity': None,
'capture_video': True,
'env_id': 'LunarLander-v2',
'total_timesteps': 50000,
'learning_rate': 0.00025,
'num_envs': 4,
'num_steps': 128,
'anneal_lr': True,
'gae': True,
'gamma': 0.99,
'gae_lambda': 0.95,
'num_minibatches': 4,
'update_epochs': 4,
'norm_adv': True,
'clip_coef': 0.2,
'clip_vloss': True,
'ent_coef': 0.01,
'vf_coef': 0.5,
'max_grad_norm': 0.5,
'target_kl': None,
'repo_id': 'Nikhitha123/cleanrl-ppo-LunarLander-v2',
'batch_size': 512,
'minibatch_size': 128}
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Evaluation results
- mean_reward on LunarLander-v2self-reported259.45 +/- 20.98