Book Details
Format
Hardcover
Pages
552
Language
English
Published
Nov 13, 2018
Publisher
Bradford Books
Edition
second edition
ISBN-10
0262039249
ISBN-13
9780262039246
Description
In this comprehensive exploration of reinforcement learning, two leading experts in the field, Richard S. Sutton and Andrew G. Barto, guide readers through the foundational concepts and advanced applications of this dynamic area of artificial intelligence. The authors take a structured approach, beginning with core principles and progressively delving into complex methodologies that define reinforcement learning. With a focus on both theoretical understanding and practical implementation, this work serves as an essential resource for students and professionals alike.
The second edition reflects the latest developments in the field, incorporating new topics and insights that have emerged since the previous release. Sutton and Barto strengthen their discussions with real-world examples, algorithms, and programming frameworks, enabling readers to grasp the implications and potential of reinforcement learning in various industries. They emphasize the adaptability and dynamic decision-making capabilities essential for developing intelligent systems.
Overall, this book not only enhances comprehension of reinforcement learning but also encourages critical thinking and innovation among readers. Users are equipped with a comprehensive toolkit for tackling complex problems through the lens of reinforcement learning, paving the way for future advancements in artificial intelligence.
The second edition reflects the latest developments in the field, incorporating new topics and insights that have emerged since the previous release. Sutton and Barto strengthen their discussions with real-world examples, algorithms, and programming frameworks, enabling readers to grasp the implications and potential of reinforcement learning in various industries. They emphasize the adaptability and dynamic decision-making capabilities essential for developing intelligent systems.
Overall, this book not only enhances comprehension of reinforcement learning but also encourages critical thinking and innovation among readers. Users are equipped with a comprehensive toolkit for tackling complex problems through the lens of reinforcement learning, paving the way for future advancements in artificial intelligence.
Genres
Science & Technology
History
Psychology