Human behavior is never an exact science, making the design and programming of artificial intelligence that seeks to replicate human behavior difficult. Usually, the answers cannot be found in sterile algorithms that are often the focus of artificial intelligence programming. However, by analyzing why people behave the way we do, we can break down the process into increasingly smaller components. We can model many of those individual components in the language of logic and mathematics and then reassemble them into larger, more involved decision-making processes. Drawing from classical game theory, "Behavioral Mathematics for Game AI" covers both the psychological foundations of human decisions and the mathematical modeling techniques that AI designers and programmers can use to replicate them. With examples from both real life and game situations, you'll explore topics such as utility, the fallacy of rational behavior, and the inconsistencies and contradictions that human behavior often exhibits. You'll examine various ways of using statistics, formulas, and algorithms to create believable simulations and to model these dynamic, realistic, and interesting behaviors in video games. Finally, you'll be introduced to a number of tools you can use in conjunction with standard AI algorithms to make it easier to utilize the mathematical models.
Dave Mark is a long-time Mac developer and author and has written a number of books on Macintosh development, including Learn C on the Macintosh, The Macintosh Programming Primer series, and Ultimate Mac Programming. His blog can be found at www.davemark.com. Jeff LaMarche is a longtime Mac developer, and Apple iPhone Developer. With over 20 years of programming experience, he's written on Cocoa and Objective-C for MacTech Magazine, as well as articles for Apple's Developer Technical Services website. He has experience working in Enterprise software, both as a developer for PeopleSoft starting in the late 1990s, and then later as an independent consultant.
