DRL(一)——Supervised Learning and Imitation
寫在前面 今天開始學習DRL了，其實RL還沒完全看完…… 大概總結一下 感覺這節課講的內容是比較初級的一些方法，從標題就看得出來，Supervised Learning，和 Imitation。 教授先是講了imitation，就是通過人類的training，建立data，然後智能體用這個data來模仿。這樣當然有很多問題，比如training中的情況可能不會包含所有的情況，總是會有新的情況出現；
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相關文章
- 1. Imitation Learning | A brief overview of Imitation Learning
- 2. Supervised learning and Unsupervised learning
- 3. imitation learning 前沿論文
- 4. Imitation Learning | 前沿論文
- 5. UFLDL Tutorial - Supervised Learning and Optimization
- 6. 《Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning》
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- 8. 機器學習 - Researchers in meta learning, imitation learning and reinforcement learning
- 9. Self-Supervised Representation Learning
- 10. 論文閱讀--Reinforced Cross-Modal Matching and Self-Supervised Imatation Learning for VLN Navigation