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Reinforcement Learning: An Overview

arxiv.org Reinforcement Learning: A Comprehensive Overview

This manuscript gives a big-picture, up-to-date overview of the field of (deep) reinforcement learning and sequential decision making, covering value-based method, policy-gradient methods, model-based methods, and various other topics (e.g., multi-agent RL, RL+LLMs, and RL+inference).

Reinforcement Learning: A Comprehensive Overview

An overview of RL published just a few days ago. 144 pages of goodies covering everything from basic RL theory to modern deep RL algorithms and various related niches.

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 methods, and various other topics (including a very brief discussion of RL+LLMs).

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