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AI Techniques for Game Programming [With CDROM] (Premier Press Game Development) [Englisch] [Taschenbuch]

Mark Collins
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Kurzbeschreibung

14. Oktober 2002 Premier Press Game Development
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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Produktinformation

  • Taschenbuch: 480 Seiten
  • Verlag: Thomson Learning; Auflage: Pap/Com (14. Oktober 2002)
  • Sprache: Englisch
  • ISBN-10: 193184108X
  • ISBN-13: 978-1931841085
  • Größe und/oder Gewicht: 23,5 x 18,7 x 2,6 cm
  • Durchschnittliche Kundenbewertung: 4.0 von 5 Sternen  Alle Rezensionen anzeigen (1 Kundenrezension)
  • Amazon Bestseller-Rang: Nr. 83.066 in Englische Bücher (Siehe Top 100 in Englische Bücher)
  • Komplettes Inhaltsverzeichnis ansehen

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Produktbeschreibungen

Pressestimmen

"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

Synopsis

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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1 von 1 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Windows specific, basic but practical 14. Februar 2003
Von Richard A
Format:Taschenbuch|Von Amazon bestätigter Kauf
As is typical of this series, 85 pages are lost to Windows specific non-AI stuff which is once again rather annoying. It would be much better (IMHO) if these sections, which are common to nearly all the books in this series, were made available online as PDFs for those who needed them. That would free up more printing space for content (or maybe reduce the price?).
As for the actual content of this book the main themes of AI are touched on with very practical examples which do work. Theory aspects are quickly skimmed over (and therefore not as heavy-going as some of the more theoretical works), but that was the intention of the author anyway. He didn't want to focus on the mathematical "why it works" but rather the more practical "how to make it work" - with some good exercises and examples thrown in.
This is a refreshing approach, and execllent as a light-ish introduction to AI. So, if you want to watch a GA evolve your first neural net in easy steps without having to know all the formulas, then this might be just the ticket.
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Amazon.com: 4.3 von 5 Sternen  23 Rezensionen
30 von 31 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Not just for games 30. April 2003
Von J. Wiest - Veröffentlicht auf Amazon.com
Format:Taschenbuch
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. ...
14 von 15 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Buckland DE-jargonises the field of AI 1. Oktober 2004
Von Cormac Mac Galloglai - Veröffentlicht auf Amazon.com
Format:Taschenbuch
This book IS my Masters thesis. I built a multi layered combative system driven wholly by neural networks evolved using genetic algorithms. The learning of agents was unsupervised and they existed collaboratively and adversarily. If all of this made no sense, dont worry! Read this book and it will.

The book covers these techniques (except for multi layered architectures) to a level understood by anyone with a basic knowledge of C++. It totally demystifies NNs and GAs. Other books on these subjects actually put you off the entire concepts of AI by feeding you fear and confusion.

I have completed the book and have read it numerous times. It is going to be invaluable for my development of PHd stuff - his writing introduces areas for potential research.

Im would definately buy other books from this author. I hope he covers other areas of AI soon and puts 'em into print.

Be jaysus, tis mighty I tell ya!!!
12 von 13 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Great Stuff 9. November 2002
Von Frank Z - Veröffentlicht auf Amazon.com
Format:Taschenbuch
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.
7 von 7 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen really good intro book for neural nets and GAs 19. Dezember 2004
Von Can Kurtulus - Veröffentlicht auf Amazon.com
Format:Taschenbuch
Although other reviewers have already pointed out everything positive about this book, I felt I also had to praise it because it's so good. It's a great introduction to neural networks and genetic algorithms. By the way the author should be congratulated for his "never include any code that you don't throughly explain" philosophy. Although it's over 400 pages because of this philosophy, you can skim/skip around 150 of them if you know some win32 programming and basic high school math/physics. The book is so concise and easy to understand that I went through it in a night and came up having a firm idea about the subject. There are also a lot of good ideas to try out throughout the book(i.e. tinkering with the source included etc.)

To put it shortly, this is a great book, it's really worth the money you spend on it.
9 von 10 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen A great resource 9. April 2003
Von Ein Kunde - Veröffentlicht auf Amazon.com
Format:Taschenbuch
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.
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