| Description |
xiv, 262 pages : illustrations ; 27 cm |
| Contents |
Ch. I. Contemporary Video Game AI -- Ch. II. An Introduction to Artificial Neural Networks -- Ch. III. Supervised Learning with Artificial Neural Networks -- Ch. IV. Case Study: Supervised Neural Networks in Digital Games -- Ch. V. Unsupervised Learning in Artificial Neural Networks -- Ch. VI. Fast Learning in Neural Networks -- Ch. VII. Genetic Algorithms -- Ch. VIII. Beyond the GA: Extensions and Alternatives -- Ch. IX. Evolving Solutions for Multiobjective Problems and Hierarchical AI -- Ch. X. Artificial Immune Systems -- Ch. XI. Ant Colony Optimisation -- Ch. XII. Reinforcement Learning -- Ch. XIII. Adaptivity within Games -- Ch. XIV. Turing's Test and Believable AI |
| Summary |
"Biologically Inspired Artificial Intelligence for Computer Games reviews several strands of modern artificial intelligence, including supervised and unsupervised artificial neural networks; evolutionary algorithms; artificial immune systems, swarms, and shows-using case studies for each to display how they may be applied to computer games. This book spans the divide which currently exists between the academic research community working with advanced artificial intelligence techniques and the games programming community which must create and release new, robust, and interesting games on strict deadlines, thereby creating an invaluable collection supporting both technological research and the gaming industry."--BOOK JACKET |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Artificial intelligence -- Computer games.
|
|
Artificial intelligence -- Biological applications.
|
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Research -- Computer games.
|
| Author |
Charles, Darryl.
|
| LC no. |
2007024492 |
| ISBN |
9781591406464 hardcover |
|
1591406463 hardcover |
|
