Average Reviews:
(More customer reviews)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. ...
Click Here to see more reviews about: AI Techniques for Game Programming (Premier Press Game Development)
"AI Techniques for Game Programming" takes the difficult topics of genetic algorithms and neural networks and explains them in plain English. Gone are the tortuous mathematic equations and abstract examples to be found in other books. Each chapter takes readers through the theory a step at a time, explaining clearly how they can incorporate each technique into their own games. After a whirlwind tour of Windows programming, readers will learn how to use genetic algorithms for optimization, path-finding, and evolving control sequences for their game agents. Coverage of neural network basics quickly advances to evolving neural motion controllers for their game agents and applying neural networks to obstacle avoidance and map exploration. Backpropagation and pattern recognition is also explained. By the end of the book, readers will know how to train a network to recognize mouse gestures and how to use state-of-the-art techniques for creating neural networks with dynamic topologies.
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