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--- |
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tags: |
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- CartPole-v1 |
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- ppo |
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- deep-reinforcement-learning |
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- reinforcement-learning |
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- custom-implementation |
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- deep-rl-course |
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model-index: |
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- name: PPO |
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results: |
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- task: |
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type: reinforcement-learning |
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name: reinforcement-learning |
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dataset: |
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name: CartPole-v1 |
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type: CartPole-v1 |
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metrics: |
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- type: mean_reward |
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value: 500.00 +/- 0.00 |
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name: mean_reward |
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verified: false |
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--- |
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# PPO Agent Playing CartPole-v1 |
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This is a trained model of a PPO agent playing CartPole-v1. |
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# Hyperparameters |
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```python |
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{'env_id': 'CartPole-v1' |
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'seed': 1 |
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'num_envs': 8 |
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'pi_hidden_layers': (64 |
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64) |
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'v_hidden_layers': (64 |
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64) |
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'learning_rate': 0.001 |
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'anneal_lr': True |
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'total_timesteps': 100000 |
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'num_steps': 32 |
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'gamma': 0.98 |
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'gae_lambda': 0.8 |
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'num_minibatches': 1 |
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'num_epochs': 20 |
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'norm_advantage': True |
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'clip_coef': 0.2 |
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'clip_vloss': True |
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'vf_coef': 0.5 |
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'ent_coef': 0.0 |
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'max_grad_norm': 0.5 |
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'target_kl': None} |
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``` |
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