An Introduction to Genetic Algorithms / Edition 1

An Introduction to Genetic Algorithms / Edition 1

4.0 1
by Melanie Mitchell
     
 

ISBN-10: 0262631857

ISBN-13: 9780262631853

Pub. Date: 02/06/1998

Publisher: MIT Press

Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It

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Overview

Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics — particularly in machine learning, scientific modeling, and artificial life — and reviews a broad span of research, including the work of Mitchell and her colleagues.

The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology,ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines.

An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.

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Product Details

ISBN-13:
9780262631853
Publisher:
MIT Press
Publication date:
02/06/1998
Series:
Complex Adaptive Systems, #13
Edition description:
Reprint
Pages:
221
Sales rank:
522,594
Product dimensions:
6.80(w) x 9.90(h) x 0.50(d)
Age Range:
18 Years

Table of Contents

Preface
Acknowledgments
1Genetic Algorithms: An Overview1
2Genetic Algorithms in Problem Solving35
3Genetic Algorithms in Scientific Models85
4Theoretical Foundations of Genetic Algorithms117
5Implementing a Genetic Algorithm155
6Conclusions and Future Directions181
Appendix A Selected General References187
Appendix B Other Resources189
Bibliography191
Index203

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An Introduction to Genetic Algorithms 4 out of 5 based on 0 ratings. 1 reviews.
Guest More than 1 year ago
This book offers a great overview of Genetic Algorithms and some applications. It does not offer exhaustive coverage of the topics, but it clearly explains the basic principles. It makes for an interesting read, and gives you enough to get started in the subject.