arXiv:2412.05265cs.AI
This manuscript gives a big-picture, up-to-date overview of the field of (deep) reinforcement learning and sequential decision making, covering value-based methods, policy-based methods, model-based methods, multi-agent RL, LLMs and RL, and various other topics (e.g., offline RL, hierarchical RL, intrinsic reward). It also includes some code snippets for training LLMs with RL.
Linked by 4 identifiable commenters in 6 comments across 5 threads, from Feb 2025 to Jun 2026. Found in 2 HN submissions from Dec 2024 to Feb 2025. Open submission discussions.
Kindly suggest some books about RL? I've already studied a lot of deep learning. Please confirm if these resoruces are good, or suggest yours: Sutton et al. - Reinforcement Learning Kevin Patrick Murphy - Reinforcement Learning, an overview https://arxiv.org/abs/2412.05265…
This one looks pretty good: https://arxiv.org/pdf/2412.05265v2, although I've only skimmed it so far.
Also worth mentioning Murphy's WIP textbook[0] focused entirely on RL, which is an outgrowth of his excellent ML textbooks. [0]: https://arxiv.org/abs/2412.05265
https://arxiv.org/abs/2412.05265 Reinforcement Learning: An Overview Kevin Murphy This manuscript gives a big-picture, up-to-date overview of the field of (deep) reinforcement learning and sequential decision making, covering value-based RL, policy-gradient methods, model-based…
* 1 point by _giorgio_ 0 minutes ago | next | edit | delete [–] https://arxiv.org/abs/2412.05265 Reinforcement Learning: An Overview Kevin Murphy This manuscript gives a big-picture, up-to-date overview of the field of (deep) reinforcement learning and sequential decision…
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> "Probabilistic Machine Learning" by Murphy [...] even if it contains virtually no deep learning in it This is confusing. Are you referring to the old 2012 version? Volumes 1 & 2 (2022-3) contain a substantial amount of deep learning [1], including relatively recent…
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