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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 and 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 will discover how to train a network to recognize mouse gestures. Finally, you’ll learn 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 new found knowledge.