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Behavioral Mathematics for Game AI Paperback – March 5, 2009


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Product Details

  • Paperback: 480 pages
  • Publisher: Cengage Learning PTR; 1st edition (March 5, 2009)
  • Language: English
  • ISBN-10: 1584506849
  • ISBN-13: 978-1584506843
  • Product Dimensions: 1.3 x 7.2 x 9 inches
  • Shipping Weight: 2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (20 customer reviews)
  • Amazon Best Sellers Rank: #366,995 in Books (See Top 100 in Books)

Editorial Reviews

Review

Behavioral Mathematics introduces a raft of important techniques from decision theory, game theory, and utility theory, and uniquely applies them to game AI. These techniques are an important part of any game AI developer's toolbox.-Paul Tozour, Game AI author

This book is an excellent introduction to using AI in games. Dave has a knack for making complex subjects accessible. The text is very clear and admirably thorough. The author has chosen - wisely - to avoid the esoteric, and focus on topics which are directly useful for making real computer games.-Richard Evans, Senior AI Architect, Electronic Arts

Game developers often use little tricks to sprinkle magic decision-making abilities throughout their AI code, without necessarily understanding the fundamentals of how it works. Dave not only documents this process on paper, but he also goes into the theoretical background behind these techniques too. For anyone wishing to know more about the maths behind common game behaviors, this is the ideal textbook on the subject.-Alex J. Champandard, Editor & Consultant, AiGameDev.com

About the Author

Dave Mark is the President and Lead Designer of Intrinsic Algorithm, LLC, an independent game development studio and AI consulting company in Omaha, NE. He has been programming since 1984 when he was in high school. Much to the dismay of his teacher, he wrote his first text adventure on the school's DEC PDP-1144. After a brief detour in the music business as a composer/arranger, keyboard player and recording engineer during the early '90s, he re-entered the technology arena in 1995. After being in the IT consulting and development world for 8 years, Dave left to start game, simulation and AI consulting company, Intrinsic Algorithm LLC with his wife, Laurie. He was a contributor to the AI Game Programming Wisdom series and is a regular columnist at AIGameDev.com.

More About the Author

Dave is the President and Lead Designer of Intrinsic Algorithm, an independent game development studio and AI consulting company in Omaha, Nebraska. He has been programming since 1985 when he was in high school. (Much to his teacher's dismay, he wrote his first text adventure on the school's DEC PDP-1144 minicomputer.)

He is the author of the book "Behavioral Mathematics for Game AI" and is a contributor to the "AI Game Programming Wisdom" and "Game Programming Gems" book series from Charles River Media. Dave is also a founding member of the AI Game Programmers Guild and has spoken at numerous conferences including being a co-adviser for the AI Summits at the annual Game Developers Conference.

Dave continues to further his education by attending the University of Life. He has no plans to graduate any time soon.

Customer Reviews

Highly recommended for anyone interested in game AI or interested in improving the behavior of their current AI system.
Michael Robbins
Dave takes a novel approach, and looks at techniques for building heuristics that evaluate the game situation and rate the various options.
Kevin Dill
Written in a very down-to-earth and easy to comprehend manner, the book was an easy read, which can't be said for all AI books.
Amazon Customer

Most Helpful Customer Reviews

17 of 17 people found the following review helpful By D. Britton on May 28, 2009
Format: Paperback
I *love* this book. I simply do not understand the negative comments left by another reviewer. Because of my interest in politics, I want to write code that mimics human behavior, but until Dave Mark's book could not find anything that really "fit." Once upon a time, I took advanced math courses--even excelled in the later ones, but that was nearly 20 years ago, and I haven't really needed that type of math since. Mark explains all the math in easy to understand English. He also provides excel spreadsheets and C++ source that can be downloaded at [...] I don't remember when I've read a book as interesting as _Behavioral Mathematics for Game AI_, and that's saying something since, although I have an advanced degree in computer science, I've never really been a lover of math.
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14 of 14 people found the following review helpful By Kenneth Shor on June 7, 2009
Format: Paperback
Behavioral Mathematics is a book that I'm sure will continue to prove its worth for many future generations of Game AI Developers. I can make that strong assertion because Dave chose, instead of writing a large tomb about a possible AI architecture, to write a book that tackles (as the title implies) the mathematics behind Game AI.

Dave gives the reader a very strong toolkit for building Game AI, and by toolkit I don't mean a large library of code (although there is plenty of code) but fundamental knowledge, such as the concept of utility and how to apply it in a very practical way. Starting from simple example decisions he builds up to much more complicated cases, constantly tying everything back into practical applications of all the concepts he introduces.

Now, I don't mean to imply that this is some dry math book. Dave constantly sprinkles in his very unique brand of humor and ties in family stories that help cement any topic he's trying to get across. I would highly recommend this book to any professional or aspiring AI Programmer, or even just a player who wants a better understanding of whats going on under the hood in his favorite game.
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21 of 23 people found the following review helpful By Kevin Dill on May 15, 2009
Format: Paperback
Truth in advertising: I was the technical editor on this book. However I don't have any further financial interest, so I have no conflict of interest in writing a review. I'm also a professional game developer with 6 titles under my belt, as well as a lecturer on the subject at several prominent universities.

There are only a handful of books on AI for Games, and the techniques used in games are quite a bit different than those used in academic AI. Most of the existing books just look at the standard architectures and topics - behavior trees, state machines, scripting, path planning, etc.

Dave takes a novel approach, and looks at techniques for building heuristics that evaluate the game situation and rate the various options. This is a critical part of decision making, it is something which most games with even moderately complex AI need to do, but it is something that up to now wasn't covered very well (if at all) in the literature.

I heartily recommend this book for anybody who's interested in learning more about how to build decision makers - whether for use in games or elsewhere. The material that is here is not something that you'll find somewhere else.
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7 of 7 people found the following review helpful By Mister J on October 28, 2009
Format: Paperback
"Behavioral Mathematics for Game AI" offers a unique examination of AI in a fun but technical and specific coverage of the subject from a mathematical perspective. While maintaining a conversational tone, the book manages to cover in depth several interesting topics and techniques.

Several ideas only touched on in other texts are given a comprehensive examination. When do rational agents fail to yield interesting behavior, and how do we deal with irrational opponents? How to we prioritize the tasks we want to accomplish, and how do we keep our agents from being erratic in their choices? Finally, how to we make sure our agents have enough variation to make them feel real?

Mr. Mark's book does not focus on some of the basic constructs common in game AI today such as state machines and behavior trees; instead, it focuses on the nuts and bolts of the math we can use to tie our agents together, augment them, and give them variety. These techniques make them more deliberate, less predictable, and pose more "interesting questions", as the author is so fond of mentioning: in short, these techniques bring AI agents to life and make them more fun to play with and against.

Dave has done a remarkable job of putting together a lot of complicated mathematical concepts in an easy to understand, pleasant to read package, and I recommend it to anyone with an interest in putting together interesting AI!
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5 of 5 people found the following review helpful By Naked Pagan on July 16, 2010
Format: Paperback
A lot what I think of a book comes from my expectations. The style, the content and the useful information that it provides me all factor into my opinion.

For starters, I do programming for a living. After 10 years of .Net Web sites and databases, I'm looking to expand my skill set. Not games, necessarily, but AI for sure. I tried a couple math books on Game theory, but they were still a few levels away from practical interpretation. This book brought it down to a level I could use.

In a nutshell, it's about how to program dice for an RPG. The scope is a little broader than that, but this is the main idea. In nontechnical language, the author discusses what the goals of AI are, how rational decisions are made, and how to use probability to generate irrational decisions to model an unpredictable world.

Math wise algebra would be a good idea, and maybe some basic understanding of calculus and statistics, but he gives sufficient background so that your understanding would not be hindered. The book doesn't really teach programming per se, so it really doesn't matter what language you use (although the examples are done in C).Specific algorithms, such was swarming and flocking, are also absent. The material here would be used after you have those ideas down...for example, you have your agents flocking, so now how does the flock decide what to do, and when?

This brings me to the one real draw back to the book. I could tolerate his jokes and stories about his kids, but I suspect some UMLs would have done wonders to make the material clearer. Use cases were almost there in his examples, but it just missed the mark. Maybe this was an attempt to keep the thinking less technical and open it to a wider market, but it is something he should have touched on.
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