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AI Techniques for Game Programming (Game Development)
 
 

AI Techniques for Game Programming (Game Development) (Paperback)

by Mat Buckland (Author) "Customer: "I've just installed Windows 3.0 ..." (more)
3.3 out of 5 stars See all reviews (3 customer reviews)

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Product details

  • Paperback: 480 pages
  • Publisher: Prima Tech; Pap/Com edition (28 Oct 2002)
  • Language English
  • ISBN-10: 193184108X
  • ISBN-13: 978-1931841085
  • Product Dimensions: 24.6 x 20.2 x 0.6 cm
  • Average Customer Review: 3.3 out of 5 stars See all reviews (3 customer reviews)
  • Amazon.co.uk Sales Rank: 276,093 in Books (See Bestsellers in Books)

    Popular in this category:

    #8 in  Books > Computing & Internet > PC & Video Games > Programming > AI (Artificial Intelligence)

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Product Description

Review
"Game programming is without a doubt the most intellectually challenging field of computer science in the world. However, we would be fooling ourselves if we said that we are 'serious' people! Writing (and reading) a game programming book, should be an exciting adventure for both the author and the reader." Andre LaMothe, Series Editor

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 – 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 discover how to train a network to recognize mouse gestures.

Finally the book explains 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 newfound knowledge.


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AI Techniques for Game Programming (Game Development)
54% buy the item featured on this page:
AI Techniques for Game Programming (Game Development) 3.3 out of 5 stars (3)
Programming Game AI by Example
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Programming Game AI by Example 4.5 out of 5 stars (4)
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Customer Reviews

3 Reviews
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Average Customer Review
3.3 out of 5 stars (3 customer reviews)
 
 
 
 
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Most Helpful Customer Reviews

 
15 of 16 people found the following review helpful:
4.0 out of 5 stars Excellent Intro to AI, 11 Jun 2003
By Lee (United Kingdom) - See all my reviews
I've been interested in getting into AI for a while, but the odd read of more traditional books on AI kept putting me off - they all lose me after several chapters of hard science and maths. This book didn't, it deals with genetic algorithms and Neural nets in a very easy way, perfect for AI beginners like me to get a good grounding.

The first third of the book is the usual primer on C++ - I skipped this chapter, and only gave the book 4 stars because of this. C++ does not interest me (I'm a java person) plus as a book focusing on AI I don't expect an intro to C++/windows programming - I wish authors of these books would make better assumptions about the likely reader.

The second third is 'genetic algorithms', very easy to follow and good examples starting with the Travelling salesman (example code is C++, but I don't mind that). It explains the basics of 'encoding' the 'genes' and how to evolve them, it also deals with different approaches to evolving a gene, the author makes it fairly clear that one approach may work for one problem, but not another.

The last third of the book is Neural nets. This was the bit that I was mostly interested in - I wanted the genetic section, but it was neural nets that I have got stuck on in the past when trying to read other books. Following a nice simple introduction of Neural Nets came the stuff on implementing them, what a breeze, I wish I had read this book a while ago. It also goes on to combine neural nets and genetic algorithms to demonstrate things like path finding. The author does bypass tricky parts, there are a couple of points he provides the maths for in a reasonably simple way and makes it quite clear that you should do further reading if you want to know the theory behind these parts, I felt this was a plus though others may find it off putting.

The book is clearly aimed at those with little knowledge of the 2 main topics covered, and does an excellent job of bringing that audience up to speed and ready to do more hard core reading if they want to become gurus. If you already feel comfortable with these 2 elements of AI then this book is probably not for you, If like me you don't know much, but want to then I recommend this strongly.

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3 of 4 people found the following review helpful:
5.0 out of 5 stars Simple, practical, inspiring, 23 Jun 2003
By Nick Economidis (Thessaloniki Greece) - See all my reviews
This is an excellent book on genetic algorithms and neural networks.

I have studied neural nets and GA, but this is the most interesting book I've read so far. It is written in such a way, that you can follow even if you have a limited (A-level) maths background. The author gives a fair programming and math explanations where needed.
If you do have a high level of programming/math background, it is easy to skip the relevant chapters.

It is the best book that gives you the 'feeling' of when and how to use these techniques, his examples are fun and easy to follow.

Unlike the rest of the LaMothe's books, this one has only a limited (just 30 pages) background on windows, and only the necessary explaining of the code.

I feel this book is very inspiring for a starter on GA and NN.
It has also managed to put together very nicely all the concepts on NN and GA that I've read during the past 8 years.

Highly recommended

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7 of 13 people found the following review helpful:
1.0 out of 5 stars Misleading, 24 Jul 2003
By A Customer
The techniques presented in this book are *not* those of a professional games programmer. The author concentrates on neural networks and genetic algorithms, two techniques which have been tried in the games industry, but which largely failed. If you want to know how to program real games AI, start elsewhere - say with AI Game Programming Wisdom.
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