Overview
- Author takes as inspiration breakthroughs in game playing, and using two-agent games to explain the full power of deep reinforcement learning
- Suitable for advanced undergraduate and graduate courses in artificial intelligence, machine learning, games, and evolutionary computing, and for self-study by professionals
- Author uses machine learning frameworks such as Gym, TensorFlow, and Keras, and provides exercises to help understand how AI is learning to play
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Table of contents (8 chapters)
Keywords
About this book
After an introduction to the core concepts, environment, and communities of intelligence and games, the book is organized into chapters on reinforcement learning, heuristic planning, adaptive sampling, function approximation, and self-play. The author takes a hands-on approach throughout, with Python code examples and exercises that help the reader understand how AI learns to play. He also supports the main text with detailed pointers to online machine learning frameworks, technical details for AlphaGo, notes on how to play and program Go and chess, and a comprehensive bibliography.
The content is class-tested and suitable for advanced undergraduate and graduate courses on artificial intelligence and games. It's also appropriate for self-study by professionals engaged with applications of machine learning and with games development. Finally it's valuable for any reader engaged with the philosophical implications of artificial and general intelligence, games represent a modern Turing test of the power and limitations of AI.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Learning to Play
Book Subtitle: Reinforcement Learning and Games
Authors: Aske Plaat
DOI: https://doi.org/10.1007/978-3-030-59238-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-59237-0Published: 22 November 2020
Softcover ISBN: 978-3-030-59240-0Published: 22 November 2021
eBook ISBN: 978-3-030-59238-7Published: 21 November 2020
Edition Number: 1
Number of Pages: XIII, 330
Number of Illustrations: 39 b/w illustrations, 72 illustrations in colour
Topics: Artificial Intelligence, Game Development, Popular Culture , Media and Communication