AI Techniques for Game Programming

Book Description
"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 you through the theory a step at a time, explaining clearly how you can incorporate each technique into your own games. After a whirlwind tour of Windows programming, you will learn how to use genetic algorithms for optimization, path-finding, and evolving control sequences for your game agents. Coverage of neural network basics quickly advances to evolving neural motion controllers for your game agents and applying neural networks to obstacle avoidance and map exploration. Backpropagation and pattern recognition is also explained. By the time you?re done, you?ll 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.


Book Info
A guide to game programming with artificial intelligence. All source code and executables from the book are on the CD-ROM. Softcover. CD-ROM included.


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 has been interested in evolutionary computing and AI 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, which provides tutorials and advice on evolutionary algorithms.


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After a whirlwind tour of Windows programming, you will learn how to use genetic algorithms for optimization, path-finding, and evolving control sequences for your game agents. Coverage of neural network basics quickly advances to evolving neural motion controllers for your game agents and applying neural networks to obstacle avoidance and map exploration. Backpropagation and pattern recognition is also explained. By the time you￯﾿ﾽre done, you￯﾿ﾽll 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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