黄世宇 0d0a8a8358 | 7 months ago | |
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README.md | 7 months ago | |
a2c.yaml | 7 months ago | |
callbacks.yaml | 7 months ago | |
dqn_cartpole.yaml | 7 months ago | |
dual_clip_ppo.yaml | 7 months ago | |
ppo.yaml | 7 months ago | |
train_a2c.py | 7 months ago | |
train_dqn_beta.py | 7 months ago | |
train_ppo.py | 7 months ago |
Users can train CartPole via:
python train_ppo.py --config ppo.yaml
To train with Dual-clip PPO:
python train_ppo.py --config dual_clip_ppo.yaml
To train with A2C algorithm:
python train_a2c.py
If you want to evaluate the agent during training and save the best model and save checkpoints, try to train with callbacks:
python train_ppo.py --config callbacks.yaml
More details about callbacks can be found in Callbacks.
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Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》