First of all, I must say that the title of this book is a bit misleading, and if it's not what you're looking for, it may be a mistake to purchase. The book is not about AI in general, but instead about two AI learning techniques that are becoming more and more used in the game programming world. These two techniques are 'Genetic Algorithms' and 'Neural Networks'. The book is about how to program these, and only these, techniques. If you are looking for a more general book on AI with a broader range AI subjects, such as pathfinding, then I would suggest a book from the AI Game Programming Wisdom series.

Having said that, this book is wonderful. Not only does it easily explain how genetic algorithms and neural networks work, it shows you step by step how to implement the techniques into your own games. It can also serve as a rather nice introduction into these subjects, as you may encounter more technical explainations of them in other texts. The CD that is included also contains many useful demos and ready-to-use C++ source code, making the examples mentioned in the book quickly accessible.

If you're thinking about buying this book, make sure that it's genetic algorithms and neural networks you want to learn more about. If it is, this book is rather thin but extremely resourceful.

The only other thing I didn't like about this book, besides the title, was the author's decision to spend the first 85 pages of the book talking about Windows Programming. I believe such a thing should not be taught in such a book, because other books can be consulted to learn more about Windows Programming. I don't think this should take a star away from the book, however, since the rest of the book is extremely well-written and resourceful.

I really don't see why so many people freak out and pretend to be all upset because it covers use of the GDI at the beginning. I'll agree that in many cases it's not particularly helpful, but I don't see why people pretend to be incapable of going past those chapters. Anyway, I like this book a lot because it gets you making things that actually work, and it doesn't do it in a way that it's impossible to figure out what the heck the author is talking about. I only rate it 4 stars because it would be better titled as "Neural Nets and Genetic Algorithms for Stuff." It doesn't cover anything other than neural nets and genetics, and it certainly doesn't seem to be limited to games.

The author demonstrates that it is possible to write about a subject as complex and academic as AI without boring your audience to tears. Believe me, I've read my share of college engineering textbooks and I did plenty of crying. The author does a fine job of explaining AI in plain English. Hey, there's nothing wrong at all with injecting a bit of humour and fluff into your writing. Learning complex, scientific subjects does NOT have to be boring and painful.

The book only covers GAs and ANNs but those are two of the hottest AI algorithms being looked at in the gaming industry. The sample programs are also quite instructive.

The only gripe I have is I thought the material on Win32 programming was unnecessary. There's a plethora of material on Win32 out there, both at the bookstore and the internet.

This is the only good book in what is a completely dreadful series. Andre LaMothe is regarded by so many as a publishing/editing/authoring god when it comes to programming books, but I really have to ask why.
This series is designed to take money from 16 year old wannabe programmers that don't know better. Most of the authors have no content, and simply come up with a title that sounds exciting to the unsuspecting public, and then fill a book with as many words as they can, and almost no content.
LaMothe and the Premiere Press team then make the books appear bigger by using large fonts, and sell them at ludicrously high prices.
I feel sorry for the poor authors that actually try to impart knowledge to their audience, although most of them do not even try.

Mat, thankfully, is the only author in the entire series that is genuinely interested in imparting useful knowledge to his audience. It is held back by the bloat required by the series, and has far too many side anecdotes with what appear to me to be little purpose other than relaxing the reader, which while a useful ploy, is somewhat out of place when trying to teach an audience. Whilst it could do with some aggressive editing, Mat does a good job introducing a set of topics that he is obviously passionate about, although I would stress that it is for beginners wanting to get a 'feel' for genetic algorithms and neural networks, not for people looking for explanations of how the various algorithms work, or why particular formulas are used.

As with all Game Development books there is a wasted section describing windows programming, but then the aim of this series (not the author's fault) is to fill a book with as many pages as possible, no matter whether there is content for it or not.

I'm hoping that the author AI Techniques for Game Programming writes a follow up book going into more details with greater explanations of the reasons behind the selections of the genetic algorithm pseudo evolutionary formulas. Very interesting stuff.

So, this is a good book for beginners, that is somewhat too wordy for my taste, but represents the only book in this series that is worth it's buying price.
It is a pity that there may be other Game Development books written by committed authors such as Mat, because due my disgust at all other Game Development books I have seen aside from this one, I have made a pact with myself never to buy another, since 'Game Design' and 'Swords and Circuitry', two others I sadly bought are the saddest cause any tree could die for. They are, bluntly, pathetic, and I am furious with Lamothe for such a dreadful series.

When I started reading this book, I was thinking why the stuff was familiar to me. Oops, it 's just a beginner guide to the Windows Programming. It talks about GDI, Dialog, Creation of Back Buffer and even the Hello World. Hey, I just want to learn AI. If I want to learn Game programming, I can read Andre LaMothe's Legendary Book. These cost 8x pages while the whole book contains 40x pages (excluding the appendix and index).
But the AI part is quite good for newbie like me. Therefore, I give it 2 stars instead of 1.

I spent the majority of the time I was reading this book thinking "This is perfect!" Just about every other book of this general type that I have read assumes I know things I don't, is a lot thicker than it needs to be, is much too simple, or is really boring. I don't think the author of this book wasted any pages at all. Everything was put forth in a concise, easy to read tone, and whenever I came across something I hadn't seen before, it was explained in short order. At the same time, he does assume that you know what you're doing, C++ programming-wise, so I didn't have to skip past anything I already knew. For what it's worth, this book created a lot of enthusiasm and confidence in me.

The examples in the book are great. Each chapter takes you through a different small project that helps you to understand what is going on, as well as how it can be applied to games. And, as a bonus, the projects are actually interesting! I really got a kick out of showing my versions of them to people. I was able to code each of them myself in a day or two as I went, but the author's full source code and executables are included if you just want to take a look as you read.

If you are already pretty familiar with windows programming, you probably won't need to read the first two chapters, but they answered a lot of questions for me, and really I felt like the author knew what I was thinking. Later on in the book, there is a review of transforms and matrix math that I found to be a really good reference and refresher.

As a side note, the author wanted to title this book "Genetic Algorithms and Neural Networks for Game Programming," but his publisher didn't think it was 'snappy' enough. He's very active in the forums on his website, and he and others there have been a great help to me.

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. ...

I work for a middle to large size game developer and found myself in a position where I had to learn about neural networks very quickly (we are experimenting with them for part of a sports sim we are developing). A colleague recommended this book and I've found it to be invaluable. I picked up the basics in just a few days, enough so I could follow the code at work, and even to suggest some improvements.

I'm was also surprised by how much fun this book makes GAs and NNs. I assumed it was going to be hard work but the author has a knack for making everything seem so easy. Learning about these techniques has also given me a whole new perspective on some AI related issues.

...In a nutshell, if you want to learn about GAs and NNs then this is a great book which will fill you with excitement and help you approach AI problems in new and interesting ways.

I would be lying if I said anything more than I was very disappointed. I had been waiting for this book to get published for a long time. The problem was visible from the sections in its table of contents: 1-Windows Programming, 2-Genetic Algorithms, 3-Neural Networks, 4-Appendixes. This book is not about different AI techniques. It is only about Genetic Algorithms and Neural Networks, which are among the most questionable techniques for games. If you want to learn about AI for games, the main option is still academic AI textbooks, which typically assume you have a BA in Computer Science. The only game AI book that I recommend is the AI Game Programming Wisdom, which is a collection of articles written mostly by game developers. There is yet to be a proper game AI textbook.

This book is a well written introduction to Genetic algorithms and Neural Networks, without the usual dependence on high level math. In just a couple of days, I have gotten a clear picture of how both genetic algoritms and neural networks can be used and implemented. The provided demos are simple enough to understand quickly, and they demonstrate the material well (imagine that--a relevant demo). On top of that, they all worked without modification on my machine.

The book does not cover the more traditional "graph search" types of AI like heuristic search and expert systems (which I think is refreshing). Instead, it focuses on the types of AI that learn or evolve. This is probably a much better approach for modern game development (unless you are writing puzzle games), and I highly recommend this book.

A much needed book for game programmers, in particular those like me who are need to be told 'simply' and in a language that can be understood.

The examples are first class and Mat is to be congratulated.

I've wanted to get into AI for a long time, and if anything this book makes me feel bad that it's so easy all of a sudden. Higher-level textbooks and math-heavy resources are far too theoretical and impractical to be of any use for game programmers. This book is all you need.

Well, Ive read about 4 chapters so far, and it is definitely a keeper. If you have no prior knowledge of AI or want to clarify and be able to implement in code the concepts of genetic algorithms and neural networks, this is definitely the book for you. Just be sure to know some C++...

Some extra stuff: The two first chapters explains windows programming. Wow!! In about 70 easily degistable pages you get the hang of windows programming!

What is great about the other two sections (genetic alg's and neural nets) is that they are explained in a very down-to-earth manner, with workable code-examples in every chapter.

What is preventing me from giving it five stars is that it initially makes a point of being written so easily that an idiot can understand it, and that a witty author and a casual style of writing will more readily impregnent the information in the readers mind. Well, the author TRIES to write in a casual way that will appeal to the average targeted reader (I assume male, 18 to 30 years of age), but unfortunately that effort only manifests itself in very occasional jokes trying to punch a hole through the otherwise stiff and professional language. Still, the material is very easily presented (even for a swedish reader), and much more casually written than virtually any book on AI so far; its just that the general tone and vocabulary is a bit more dull than it had to be.

Well, regardless of this criticism, this is the best book for anybody who wants to get a clear grasp of AI, and be able to implement it in code. BUY IT!!

After reading (and enjoying) the author's web tutorials some time ago I was looking forward to receiving this book - and it hasn't disappointed.

The author has managed to squeeze in a pile of information about GAs and neural nets and yet managed to keep the math down to a minimum - which for a moron like me is especially good news! The source code is kept simple and is very easy to follow.

The example programs that accompany each chapter illustrate each technique very well, and more to the point have given me many ideas to try out with my own projects. The mouse gesture recognition example in particular is a great way of teaching backpropagation, something I had completely failed to understand until I read this book.