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An Introduction to Genetic Algorithms (Complex Adaptive Systems) [Hardcover]

Melanie Mitchell (Author)
4.8 out of 5 stars  See all reviews (5 customer reviews)

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Product details

  • Hardcover: 218 pages
  • Publisher: MIT Press (1 April 1996)
  • Language English
  • ISBN-10: 0262133164
  • ISBN-13: 978-0262133166
  • Product Dimensions: 26.1 x 18.3 x 1.9 cm
  • Average Customer Review: 4.8 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Bestsellers Rank: 1,339,549 in Books (See Top 100 in Books)

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Melanie Mitchell
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Product Description

Review

"This is the best general book on Genetic Algorithms written to date. It covers background, history, and motivation; it selects important, informative examples of applications and discusses the use of Genetic Algorithms in scientific models; and it gives a good account of the status of the theory of Genetic Algorithms. Best of all the book presents its material in clear, straightforward, felicitous prose, accessible to anyone with a college-level scientific background. If you want a broad, solid understanding of Genetic Algorithms--where they came from, what's being done with them, and where they are going--this is the book.--John H. Holland, Professor, Computer Science and Engineering, and Professor of Psychology, The University of Michigan; External Professor, the Santa Fe Institute.

Review

"An outstanding introduction to a new and important field of computer science." Tim Watson , The Computer Journal "This is a useful introduction to the subject and is well worth reading as an entry into evolutionary computing." Chris Robbins , Computing "This is the best general book on Genetic Algorithms written to date. It covers background, history, and motivation; it selects important, informative examples of applications and discusses the use of Genetic Algorithms in scientific models; and it gives a good account of the status of the theory of Genetic Algorithms. Best of all the book presents its material in clear, straightforward, felicitous prose, accessible to anyone with a college-level scientific background. If you want a broad, solid understanding of Genetic Algorithms--where they came from, what's being done with them, and where they are going--this is the book. John H. Holland, Professor, Computer Science and Engineering,and Professor of Psychology, The University of Michigan;External Professor, the Santa Fe Institute. --This text refers to the Paperback edition.
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Most Helpful Customer Reviews
14 of 14 people found the following review helpful
By A Customer
Format:Hardcover
From the very first page Mitchell has the reader hooked as she unleashes the various applications of GAs. With each example the various elements of GAs are illustrated, making it an enjoyable but still very educational experience. The technical material is not too hard to follow, and the mathematical proofs presented are easy to understand given a modest background in maths. I recommend this book as a first read for anyone who is interested in learning more about GAs, and an entertaining read for the GA veterans.
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8 of 8 people found the following review helpful
Format:Paperback
This is the book that launched my interest in GA's, it took a subject that I expected to bored to tears with and totally engaged me, I just couldn't put this book down. The authors style makes for easy reading but at the same time does not skimp on detail. A very good starting point for anyone looking to introduce themselves to the subject and jam packed with usefull references for those wishing to study further.
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3 of 3 people found the following review helpful
By A Customer
Format:Hardcover
This book is ideal for someone totally new to the field of GAs. Mitchell begins with the fundamental concepts of the simple GA and proceeds to survey a wide variety of applications. I especially enjoyed the coverage of topics related to machine intelligence, which are sometimes left out in books that focus solely on optimization. The book contains enough information for someone with programming experience to code their own GA (including suggested computer exercises), although no source code is presented. However, the background gained from reading Mitchell's book will enable an easier read of more technical books (which may include source code implementations).
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