Mathematical Foundations of Reinforcement Learning (Hardcover)
暫譯: 強化學習的數學基礎 (精裝版)

Zhao, Shiyu

Mathematical Foundations of Reinforcement Learning (Hardcover)

商品描述

This book provides a mathematical yet accessible introduction to the fundamental concepts, core challenges, and classic reinforcement learning algorithms. It aims to help readers understand the theoretical foundations of algorithms, providing insights into their design and functionality. Numerous illustrative examples are included throughout. The mathematical content is carefully structured to ensure readability and approachability.

The book is divided into two parts. The first part is on the mathematical foundations of reinforcement learning, covering topics such as the Bellman equation, Bellman optimality equation, and stochastic approximation. The second part explicates reinforcement learning algorithms, including value iteration and policy iteration, Monte Carlo methods, temporal-difference methods, value function methods, policy gradient methods, and actor-critic methods.

With its comprehensive scope, the book will appeal to undergraduate and graduate students, post-doctoral researchers, lecturers, industrial researchers, and anyone interested in reinforcement learning.

商品描述(中文翻譯)

這本書提供了一個數學性但易於理解的介紹，涵蓋強化學習的基本概念、核心挑戰和經典演算法。它旨在幫助讀者理解演算法的理論基礎，並提供對其設計和功能的深入見解。書中包含了許多示例以作說明。數學內容經過精心結構化，以確保可讀性和易接近性。

本書分為兩個部分。第一部分探討強化學習的數學基礎，涵蓋貝爾曼方程（Bellman equation）、貝爾曼最優方程（Bellman optimality equation）和隨機近似（stochastic approximation）等主題。第二部分詳細說明強化學習演算法，包括價值迭代（value iteration）和策略迭代（policy iteration）、蒙地卡羅方法（Monte Carlo methods）、時間差分方法（temporal-difference methods）、價值函數方法（value function methods）、策略梯度方法（policy gradient methods）和行為者-評論者方法（actor-critic methods）。

本書的內容範圍廣泛，將吸引本科生、研究生、博士後研究人員、講師、工業研究人員以及任何對強化學習感興趣的人士。

作者簡介

Shiyu Zhao is currently an Associate Professor and Director of the Intelligent Unmanned Systems Laboratory in the School of Engineering at Westlake University, Hangzhou, China. He received his Ph.D. degree in Electrical and Computer Engineering from the National University of Singapore in 2014. Before joining Westlake University in 2019, he was a Lecturer in the Department of Automatic Control and Systems Engineering at the University of Sheffield, UK. His primary research interest lies in decision-making and sensing of multi-robot systems.

作者簡介(中文翻譯)

施宇趙目前是中國杭州西湖大學工程學院的副教授及智能無人系統實驗室主任。他於2014年在新加坡國立大學獲得電機與計算機工程博士學位。在2019年加入西湖大學之前，他曾擔任英國謝菲爾德大學自動控制與系統工程系的講師。他的主要研究興趣在於多機器人系統的決策與感知。

類似商品

最後瀏覽商品 (20)