Hugging Face 深度強化學習（Deep RL）入門指南與核心概念解析
Original: An Introduction to Deep Reinforcement Learning
This article is the introductory first chapter of the official Hugging Face "Deep Reinforcement Learning Course." With the widespread…
本指南為 Hugging Face 深度強化學習課程的第一章。文章系統性地介紹了強化學習（RL）的核心架構，包含 Agent 與環境的互動循環、獎勵機制，並深入探討「探索與利用」（Exploration vs. Exploitation）的權衡。最後介紹如何結合深度學習形成 Deep RL，並引導讀者使用 Stable-Baselines3 等開源工具進行實作。
This article is the introductory first chapter of the official Hugging Face "Deep Reinforcement Learning Course." With the widespread adoption of RLHF (Reinforcement Learning from Human Feedback) for aligning large language models (LLMs) in recent years, understanding the fundamental principles of reinforcement learning (RL) has become more important than ever.
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