Reinforcement Learning: An Overview

Abstract

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.

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• arxiv keymurphy2024reinforcement

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