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The best lectures on Reinforcement Learning and related topics are by Dimitris Bertsekas: https://web.mit.edu/dimitrib/www/home.html https://web.mit.edu/dimitri
by dualofdual 2y ago
The best lectures on Reinforcement Learning and related topics are by Dimitris Bertsekas: https://web.mit.edu/dimitrib/www/home.html https://web.mit.edu/dimitrib/www/home.html
- rybthrow2 2y agoAlso one by David Silver of Deepmind, AlphaGo fame are good too: https://www.youtube.com/watch?v=2pWv7GOvuf0 https://www.youtube.com/watch?v=2pWv7GOvuf0
- esafak 2y agoHis books tend to be dry and geared towards researchers, in my opinion. He has a new one on RL: https://web.mit.edu/dimitrib/www/RLCOURSECOMPLETE%202ndEDITION.pdf https://web.mit.edu/dimitrib/www/RLCOURSECOMPLETE%202ndEDITI...
- joe_lin 2y agoI'm looking for content (researcher myself) -- mainly on the application side. Should I start with this one? Or anything else? Very curious about RL for LLMs for example (using data from real use).
- esafak 2y agoI have not read it but it looks like a comprehensive reference. For a more applied treatment see Foundations of Deep Reinforcement Learning. https://slm-lab.gitbook.io/slm-lab/publications-and-talks/instruction-for-the-book-+-intro-to-rl-section https://slm-lab.gitbook.io/slm-lab/publications-and-talks/in... Neither cover LLMs. I don't follow the literature closely so I can only suggest you read papers: https://github.com/WindyLab/LLM-RL-Papers https://github.com/WindyLab/LLM-RL-Papers
- forkerenok 2y agoWould you mind explicitly indicating whether you have reviewed the submitted materials? And if so, why is it inferior to the material you linked? Not trying to catch you, genuine interest.
- richard___ 2y agoNo. They are outdated and focused on strange things. You wont understand ppo from his textbooks
- cplat 2y agoWhich aspects? Foundational textbooks would focus on principles, not necessarily implementations, and don't go "outdated" the same way a snippet does.