DRL(一)——Supervised Learning and Imitation
写在前面 今天开始学习DRL了，其实RL还没完全看完…… 大概总结一下 感觉这节课讲的内容是比较初级的一些方法，从标题就看得出来，Supervised Learning，和 Imitation。 教授先是讲了imitation，就是通过人类的training，建立data，然后智能体用这个data来模仿。这样当然有很多问题，比如training中的情况可能不会包含所有的情况，总是会有新的情况出现；
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相关文章
- 1. Imitation Learning | A brief overview of Imitation Learning
- 2. Supervised learning and Unsupervised learning
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- 4. Imitation Learning | 前沿论文
- 5. UFLDL Tutorial - Supervised Learning and Optimization
- 6. 《Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning》
- 7. 【RL】8.Imitation Learning
- 8. 机器学习 - Researchers in meta learning, imitation learning and reinforcement learning
- 9. Self-Supervised Representation Learning
- 10. 论文阅读--Reinforced Cross-Modal Matching and Self-Supervised Imatation Learning for VLN Navigation