• Title: Mathematical Foundations of Reinforcement Learning
• Author(s) Shiyu Zhao
• Publisher: Springer (2025); eBook (Online Eition by GitHub
• Paperback: 291 pages
• eBook: PDF (19 MB), PDF Files, Video Lectures (YouTube)
• Language: English
• ISBN-10: 9819739438
• ISBN-13: 978-9819739431
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Book Description

This book provides a mathematical yet accessible introduction to the fundamental concepts, core challenges, and classic Reinforcement Learning (RL) 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.

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• Reinforcement Learning
• Machine Learning
• Algorithms and Data Structures
• Neural Networks and Depp Learning
• Artificial Intelligence
• Statistics, Mathematical Statistics, and SAS Programming
• Probability and Stochastic Processe

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