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Other titles in the Complex Adaptive Systems series:

An Introduction to Genetic Algorithms (Complex Adaptive Systems)

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An Introduction to Genetic Algorithms (Complex Adaptive Systems) Cover

 

Synopses & Reviews

Publisher Comments:

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.

Synopsis:

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.

Product Details

ISBN:
9780262631853
Author:
Mitchell, Melanie
Publisher:
A Bradford Book
Location:
Cambridge
Subject:
Computer Science
Subject:
Programming - General
Subject:
Genetic algorithms
Subject:
Genetics
Subject:
Mathematical models
Subject:
Genetics -- Mathematical models.
Subject:
Software Engineering - Programming and Languages
Edition Description:
Trade paper
Series:
Complex Adaptive Systems An Introduction to Genetic Algorithms
Publication Date:
19980302
Binding:
Paperback
Grade Level:
from 17
Language:
English
Illustrations:
Y
Pages:
221
Dimensions:
9.9 x 6.8 x 0.5 in

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Related Subjects

Computers and Internet » Artificial Intelligence » Artificial Life
Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Computers and Internet » Personal Computers » General
Computers and Internet » Software Engineering » Algorithms
Computers and Internet » Software Engineering » General
Computers and Internet » Software Engineering » Programming and Languages

An Introduction to Genetic Algorithms (Complex Adaptive Systems) New Trade Paper
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Product details 221 pages Bradford Book - English 9780262631853 Reviews:
"Synopsis" by , 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.
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