AI for Computer Games and Animation: A Cognitive Modeling Approach [Hardcover]

John David Funge (Author)

Book Description

ISBN-10: 1568811039 | ISBN-13: 978-1568811031 | Publication Date: August 15, 1999 | Edition: 1

John Funge introduces a new approach to creating autonomous characters. Cognitive modeling provides computer-animated characters with logic, reasoning, and planning skills. Individual chapters in the book provide concrete examples of advanced character animation, automated cinematography, and a real-time computer game. Source code, animations, images, and other resources are available at the book's website, listed below.

Editorial Reviews

Amazon.com Review

Simply put, AI for Games and Animation: A Cognitive Modeling Approach shows how video game characters can be taught to "think" for themselves. This groundbreaking title points the way for the future of intelligent gaming. While this book features formal mathematical proofs of its arguments, it also provides a worthwhile overview of how today's video game characters are currently programmed, as well as future possibilities for making them "smarter" (and more realistic) through techniques borrowed from AI and robotics. At this level, the text shows off the possibility of adding cognitive models (expressed in the author's own Cognitive Modeling Language, CML) to the games of the near future.

While today's games feature behavior models and incorporate the rules of physics to create realistic scenes, this book makes a strong case that by adding intelligence to characters, game realism can be enhanced further while actually simplifying development. Though this book is certainly worthy as an academic treatise on the subject, the author keeps an eye on real-world programming issues. For instance, he suggests that adding AI to game characters will coexist with current programming techniques. He is also careful to pay attention to the limits of CPU and graphics processing power when suggesting new algorithms.

The most abstract sections here show off the mathematical techniques (and modeling language) for adding knowledge representation, sensing, and learning to characters. Later sections offering two simulated worlds (featuring T-Rexes and raptors, for example) show off the author's argument to good advantage.

Though it requires a background in math to appreciate fully, AI for Games and Animation can be read profitably by anyone interested in the future of gaming. It is only a matter of time before games adopt some of the techniques presented here, and serious game developers will get a head start with this intriguing and groundbreaking book. --Richard Dragan

Topics covered: Cognitive modeling for games and simulations, geometric and behavior models, domain knowledge, sensing, interval arithmetic basics, creating nondeterministic behavior, Cognitive Modeling Language (CML), and sample model worlds.

Product Details

• Hardcover: 220 pages
• Publisher: A K Peters/CRC Press; 1 edition (August 15, 1999)
• Language: English
• ISBN-10: 1568811039
• ISBN-13: 978-1568811031
• Product Dimensions: 8.9 x 5.9 x 0.6 inches
• Shipping Weight: 1 pounds
• Average Customer Review: 2.9 out of 5 stars  See all reviews (10 customer reviews)
• Amazon Best Sellers Rank: #2,539,342 in Books (See Top 100 in Books)

More About the Author

John Funge (www.jfunge.com) is a co-founder and one of the lead scientists at a new Silicon Valley based company focusing on AI effects for computer entertainment. John previously worked at Sony Computer Entertainment America's (SCEA) research lab. Before that John was a member of Intel's Microcomputer Research Lab (MRL). He received a B.Sc. in Mathematics and Computer Science from King's College London in 1990, an M.Sc. in Computation from Oxford University in 1991, and a Ph.D. in Computer Science from the University of Toronto in 1998. For his Ph.D. John successfully developed a new approach to high-level control of characters in games and animation. John is the author of numerous technical papers and two books, including his new book Artificial Intelligence for Computer Games: An Introduction (www.ai4games.org). John is the Associate Editor for AI and Goal-Directed Action Planning for the International Journal of Intelligent Games and Simulation (IJIGS) and a member of the International Game Developers Association (IGDA) Artificial Intelligence Interface Standards Committee (AIISC). His current research interests include computer games, machine learning, knowledge representation and new democratic methods.

Customer Reviews

Most Helpful Customer Reviews

25 of 28 people found the following review helpful:

2.0 out of 5 stars Good for references, not much else..., November 5, 1999

By 

LG (Redwood City, CA United States) - See all my reviews

This review is from: AI for Computer Games and Animation: A Cognitive Modeling Approach (Hardcover)

When I bought this book I wasn't quite sure what to expect since the title, "AI for Games and Animation: ..." is so broad sounding. What I did expect was that it would be written in an easy to read form and hopefully provide enough in-depth coverage of the topics so that a reasonable game programmer could implement them based on the information provided, without further research. This criteria seems to be adhered to in the technical articles in a publication such as Game Developer.

Apparently, no-one bothered to tell Mr. Funge about this. Although the book does provide some case studies (examples) the actual details of their implementations are often glossed over or shrouded in unnecessary mathematical formalism that is out of place in a game programmer's book. To give an example, complex topics such as inverse kinematics and coupled spring systems are given several short paragraphs. In describing coupled spring systems for deforming a mesh, Funge uses "x dot" notation that most game programmers probably are not familiar with.

The only saving grace is the reference section which can point the reader to more specific literature that may actually be helpful in constructing implementations of some of the techniques described in the book. This increases the rating from the worst (1 star) to 2 stars since it is actually pretty comphrensive.

20 of 22 people found the following review helpful:

2.0 out of 5 stars Not really useful for game programmers, September 5, 2000

By A Customer

This review is from: AI for Computer Games and Animation: A Cognitive Modeling Approach (Hardcover)

The title of this book is its biggest flaw because it appears to cater to game programmers but the techniques described within it are not that useful. It appears that the book is marketed to the game programming community due to its immense size. Anybody interested it this book would be well advised to purchase the siggraph proceedings that it comes from because not only will you learn what this book is about, you will also have a large resource of other techniques that can be used for graphics and animation.

Yes, John's technique is interesting and different ... however he does not have a gaming background, has never worked on games, and it is obvious that this book is simply an extension of a research paper. You can find better resources for both AI and game programming elsewhere.

13 of 15 people found the following review helpful:

2.0 out of 5 stars All The AI Concepts No One Actually Uses In One Short Book, December 9, 1999

By A Customer

This review is from: AI for Computer Games and Animation: A Cognitive Modeling Approach (Hardcover)

This book is a fascinating mixture of perfectly reasonable AI techniques which are seldom useful for games, combined with useful but obvious techniques which are described better in a standard AI textbook.

Overall, this book suffers greatly from a lack of relevance. There is no pseudocode, and the few examples in the book are poorly chosen and generally not representative of the real problems encountered in game AI programming. Similarly, many of the valuable techniques often used in game AI are not even mentioned.

The book gives a brief overview of breadth-first, best-first, and depth-first search, but it entirely omits mention of the A* algorithm, some form of which is used in nearly every game that involves pathfinding.

The book also covers a number of topics that are entirely out of place in a book about game AI. Chapter 2 is entirely devoted to game physics. Chapter 6 covers machine learning, a technique which is seldom used for games. And Chapter 11 covers texture mapping and deformable models, which, although important for games, have nothing to do with AI.

The book does have some high points, such as the and the introduction to interval arithmetic. But even then, it wastes the reader's time with several pages of unnecessary mathematical proofs.

Overall, I recommend avoiding this book. Not only will it not inform the reader, it presents a misguided notion of what game AI is all about.