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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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About the Author
Mat Buckland studied Computer Science at London University, then spent many years as a Risk Management Consultant. He went on to work for a developer producing games for Gremlin Software. He now works as a Freelance programmer and AI consultant. Mat bas been interested in evolutionary computing and Al in general since he first read about these techniques back in the early '80s. He is the author of the ai-junkie.com Web Site (www.ai-junkie.com), which provides tutorials and advice on evolutionary algorithms.
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- PublisherPrima Tech
- Publication date2002
- ISBN 10 193184108X
- ISBN 13 9781931841085
- BindingPaperback
- LanguageEnglish
- Number of pages480
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