AI Techniques for Game Programming

AI Techniques for Game Programming

by Mat Buckland, Mark Collins
     
 


"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 readers through the theory a step at a time, explaining clearly how they can incorporate each technique into… See more details below

Overview


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

ISBN-13:
9781931841085
Publisher:
Cengage Learning
Publication date:
10/14/2002
Series:
The Premier Press Game Development Series
Edition description:
BOOK & CD
Pages:
480
Product dimensions:
7.36(w) x 9.26(h) x 1.01(d)

Table of Contents


Introduction Part 1: Windows Programming 1. In the Beginning, There Was a Word, and the Word Was Windows 2. Further Adventures With Windows Programming Part 2: Genetic Algorithms 3. An Introduction to Genetic Algorithms 4. Permutation Encoding and the Traveling Salesman Problem 5. Building a Better Genetic Algorithm 6. Moon Landing Made Easy Part 3: Neural Networks 7. Neural Networks in Plain English 8. Giving Your Bot Senses 9. A Supervised Training Approach 10. Real-Time Evolution 11. Evolving Neural Topology Appendices: A: Web Resources B: Bibliography and Recommende Reading C: What's On the CD

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