Review of AI Techniques for Game Programming (The Premier Press Game Development Series) (Paperback)

Beauty is in the eye of the beholder, so let me tell you what I was looking for:a non-academic AI book with practical examples for implementing genetic algorithms and neural nets.I don't have a math degree (though I understand basic algebra and remember a bit of trig), and I learn best by doing hand's on project, not by theorizing.

This book fits the bill perfectly.It is well written, humorous, clear and patient.The examples are interesting enough that you can see how they would be useful for solving other problems, not necessarily game related.

One caveat:if you don't have a decent intro to basic Win32 API programming, get Charles Petzold's Programming Win32 book and get busy.Yes, the first two chapters of AI Techniques are a Win32 refresher (which was good for me because I last wrote Win32 3 years ago...I now do Java only), but I'm pretty sure if you haven't seen it before you'll be lost.

BTW, just to give you an idea how clear the concepts were presented, I've recoded Chapters 3 and 5 as properly OOPed (MVC, etc) Java applications.Just MHO, but Java is a much better platform for this stuff. ...

Product Description
AI Techniques for Game Programming takes the difficult topics of genetic algorithms and neural networks, explaining them in plain English. Gone are the tortuous mathematic equations and abstract examples to be found in other books. Each chapter will take you through the theory a step at a time using fun, practical examples and providing you with all the knowledge you require to start incorporating these esoteric techniques into your own games and applications.

After a whirlwind tour of Windows programming for those readers who require a refresher, you will learn how to use genetic algorithms for optimization, path-finding and evolving control sequences for your game agents. After learning the basics of neural networks, AI Techniques for Game Programming will demonstrate how you can evolve neural motion controllers for your game agents, and how neural networks may be applied to obstacle avoidance and map exploration. You will learn about backpropagation and pattern recognition and will discover how to train a network to recognize mouse gestures. Finally, you'll learn state-of-the-art techniques for creating neural networks with dynamic topologies.

Each chapter is complimented by well-commented source code and most provide fun exercises and problems for you to practice your new found knowledge.

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