- Hardcover: 896 pages
- Publisher: CRC Press; 2 edition (August 6, 2009)
- Language: English
- ISBN-10: 0123747317
- ISBN-13: 978-0123747310
- Product Dimensions: 7.8 x 1.5 x 9.5 inches
- Shipping Weight: 4 pounds (View shipping rates and policies)
- Average Customer Review: 21 customer reviews
- Amazon Best Sellers Rank: #218,402 in Books (See Top 100 in Books)
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Artificial Intelligence for Games 2nd Edition
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"Ian Millington's book is a comprehensive reference to the most widely used techniques in game AI today. Any game developer working on AI will learn something from this book, and game producers should make sure their AI programmers have a copy." -Dr. Ian Lane Davis, Mad Doc Software
About the Author
Ian Millington is a partner of IPR Ventures, a consulting company developing next-generation AI technologies for entertainment, modeling, and simulation. Previously he founded Mindlathe Ltd, the largest specialist AI middleware company in computer games, working with on a huge range of game genres and technologies. He has a long background in AI, including PhD research in complexity theory and natural computing. He has published academic and professional papers and articles on topics ranging from paleontology to hypertext.
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This book is one of the few exceptions. There is a refreshing breadth and depth of game AI knowledge in this book that has been of tremendous help. Unlike the common "Gems" series of books, this book contains enough information on nearly every topic for the reader to build a 'ground up' implementation of their own.
My only complaints are that the pseudocode seems to be overly simplified and not as easily converted to a concrete implementation as I'd like, and that even for a book on game-specific AI implementations, the authors seem to enjoy a bit more of an academic/idealized approach to the design. That might be less bothersome to a professional game developer, but I'm at the hobbyist/indie level, and sometimes need a quick-and-dirty implementation before I begin to really understand what's going on.
Having said that, I was able to use the book to learn about and implement goal-oriented action planning, fast and flexible A* path finding (with additional info on modified funnel algorithm online), and several other critical components.
I would absolutely recommend this book.
I have a couple of small gripes with the book: the pseudocode contains a number of errors (e.g., an incorrect sign or off-by-one error), and the section on neural networks failed to fully convey how useless these really are. But on the whole, it was a great read, with real value on every page. If you're thinking about writing AI for any game, you should start with this book.
I'm not willing to implement those, because I'm more focused on web and data analysis, but the techniques explained here in how to cheat the user are really great and can be applied in the way of thinking when you face a problem in your daily work tasks.