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Searching... | 30000004382713 | QA76.618 E86 2000 | Open Access Book | Book | Searching... |
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Summary
Summary
Worldwide interest in the applications of evolutionary computing techniques to the design of engineering and information systems grows each day. Pattern recognition, control systems, factory scheduling, automation, generation of computer programs, and the design of intelligent paradigms all benefit from evolutionary techniques-their potential applications indeed seem limited only by the imaginations of scientists and engineers.
This is an area of intensive research and development, and evolutionary computing techniques are themselves constantly evolving. It becomes important, then, that computer scientists and applications engineers have a working knowledge of the techniques, stay abreast of recent advances, and have the opportunity to incorporate them into their own systems and designs.
Evolution of Engineering and Information Systems and Their Applications fills this need by providing an overview of the field and offering state-of-the-art reviews of the most important techniques and applications of evolutionary computing. The top experts from around the world discuss developments in genetic algorithms, genetic programming, and evolutionary strategies and applications including VLSI CAD, robot sensors, neural networks, and fuzzy classification systems.
This is a new and very hot field, yet there are few-if any-resources that document and disseminate its advances. With Evolution of Engineering and Information Systems and Their Applications, you have the opportunity to learn from the leading authorities, use these powerful techniques to improve your own systems, and help evolutionary computing reach its nearly boundless potential.
Table of Contents
Preface | |
Chapter 1 An Introduction to Evolutionary Computing | p. 1 |
Chapter 2 The Evolution of Concurrent Systems | p. 31 |
Chapter 3 Exploring the Design Space of Artificial Self-Replicating Structures | p. 65 |
Chapter 4 Evolutionary Approaches to the Learning of Fuzzy Rule-Based Classification Systems | p. 105 |
Chapter 5 Synthesis of Neural Networks Using a Two-Dimensional Approach | p. 161 |
Chapter 6 Some Experiments in the Evolution of Robot Sensors | p. 191 |
Chapter 7 Evolution of Neural Network Modules: ATR's Artificial Brain Project | p. 229 |
Chapter 8 VLSI CAD and the Integration of Evolutionary Techniques | p. 275 |
Index | p. 313 |