Genetic Algorithms in Search, Optimization, and Machine Learning 1st Edition

4.2 out of 5 stars 24 ratings
ISBN-13: 978-0201157673
ISBN-10: 0201157675
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  • Genetic Algorithms in Search, Optimization, and Machine Learning
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  • A Field Guide to Genetic Programming
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Editorial Reviews Review

David Goldberg's Genetic Algorithms in Search, Optimization and Machine Learning is by far the bestselling introduction to genetic algorithms. Goldberg is one of the preeminent researchers in the field--he has published over 100 research articles on genetic algorithms and is a student of John Holland, the father of genetic algorithms--and his deep understanding of the material shines through. The book contains a complete listing of a simple genetic algorithm in Pascal, which C programmers can easily understand. The book covers all of the important topics in the field, including crossover, mutation, classifier systems, and fitness scaling, giving a novice with a computer science background enough information to implement a genetic algorithm and describe genetic algorithms to a friend.

From the Back Cover

This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.

Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs. No prior knowledge of GAs or genetics is assumed, and only a minimum of computer programming and mathematics background is required.


Product details

  • Item Weight : 1.92 pounds
  • Hardcover : 432 pages
  • ISBN-10 : 0201157675
  • ISBN-13 : 978-0201157673
  • Product Dimensions : 7.75 x 0.81 x 9.53 inches
  • Publisher : Addison-Wesley Professional; 1st Edition (January 11, 1989)
  • Language: : English
  • Customer Reviews:
    4.2 out of 5 stars 24 ratings
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