Reinforcement Learning Explained: A Practical Problem-Solving Approach
暫譯: 強化學習解析：實用問題解決方法
Hellgren, Jonas, Lindgren, Johannes
- 出版商: CRC
- 出版日期: 2026-06-29
- 售價: $2,240
- 貴賓價: 9.5 折 $2,128
- 語言: 英文
- 頁數: 272
- 裝訂: Quality Paper - also called trade paper
- ISBN: 103299665X
- ISBN-13: 9781032996653
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相關分類:
Reinforcement
尚未上市，無法訂購
相關主題
商品描述
Reinforcement Learning (RL) is a branch of Artificial Intelligence (AI) where agents learn optimal behavior through interaction with an environment by receiving feedback in the form of reward. After decades of research, RL has matured into a powerful technology driving real-world innovation; it is now used in areas such as robotics, energy systems, finance, and autonomous vehicles.
Yet, for many, RL feels inaccessible, buried under dense mathematics and complex theory. This book changes that. It is designed to help newcomers start applying RL as quickly as possible through a classical pedagogical approach: many small, focused examples that build intuition and practical skill step by step.
Featuring:
- Essential concepts explained from the ground up
- Code-based examples that reveal how algorithms work in practice
- Worked examples by hand to strengthen intuition, just like in engineering or mathematics textbooks
- Language-agnostic guidance, easily followed using Python, Java, or C++
Even readers without coding or university-level mathematics backgrounds will gain valuable insight into the fascinating world of RL--insight that may become a critical differentiator in the age of AI. Whether you are a student or professional, Reinforcement Learning Explained will give you the tools and confidence to explore one of AI's most exciting frontiers.
商品描述(中文翻譯)
強化學習（Reinforcement Learning, RL）是人工智慧（Artificial Intelligence, AI）的一個分支，代理人透過與環境互動並接收獎勵形式的反饋來學習最佳行為。經過數十年的研究，強化學習已經發展成為推動現實世界創新的強大技術；目前它被應用於機器人技術、能源系統、金融和自動駕駛車輛等領域。
然而，對許多人來說，強化學習似乎難以接觸，因為它被繁瑣的數學和複雜的理論所掩蓋。本書改變了這一點。它旨在幫助新手儘快開始應用強化學習，採用經典的教學方法：許多小而專注的範例，逐步建立直覺和實用技能。
本書特色：
- 從基礎開始解釋的基本概念
- 基於程式碼的範例，揭示演算法在實踐中的運作方式
- 手動計算的範例以增強直覺，與工程或數學教科書類似
- 語言無關的指導，使用 Python、Java 或 C++ 都能輕鬆跟隨
即使是沒有程式設計或大學數學背景的讀者，也能獲得對強化學習這個迷人世界的寶貴見解——這些見解在人工智慧時代可能成為關鍵的區別因素。無論您是學生還是專業人士，《強化學習解說》將為您提供探索人工智慧最令人興奮的前沿之一所需的工具和信心。
作者簡介
Jonas Hellgren is a researcher specializing in reinforcement learning, optimization, and electrified vehicle systems. With experience across academia and industry spanning patents, publications, thesis supervision, and industrial projects, he brings both practical insight and theoretical depth. This book reflects his commitment to making complex ideas accessible.
Johannes Lindgren is a technical consultant specializing in software development, verification, and commissioning across rail, automotive, and maritime applications. Currently at Combine, developing software for the rail sector. Previous roles include simulation and verification at Volvo Autonomous Solutions and system commissioning at Lean Marine, along with research in image segmentation at CPAC Systems.
作者簡介(中文翻譯)
Jonas Hellgren 是一位專注於強化學習、優化和電動車系統的研究員。他在學術界和產業界擁有豐富的經驗，涵蓋專利、出版物、論文指導和工業專案，帶來了實用的見解和理論的深度。本書反映了他致力於使複雜概念變得易於理解的承諾。
Johannes Lindgren 是一位專注於軟體開發、驗證和調試的技術顧問，涵蓋鐵路、汽車和海事應用。目前在 Combine 工作，為鐵路領域開發軟體。之前的職位包括在 Volvo Autonomous Solutions 進行模擬和驗證，以及在 Lean Marine 進行系統調試，並在 CPAC Systems 進行影像分割的研究。
