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am 15. Juni 2000
This is an excellent introductory book on genetic algorithms. It's very concisely written and there are a ton of interesting projects and programs to do. I've done a few of them myself and learned a lot. This book is one of those that I keep going back to and I always find some new idea or thing to try out.

If you're a programmer and have been thinking of getting into genetic algorithms, you won't go wrong with this book. Very highly recommended.
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am 31. Mai 1999
This book provides an extremely good introductin to people not familiar with GA. No source code is presented; if done, the book will be a complete one.Nevertheless it provides useful guidelines for implementors.
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am 27. Mai 1999
Good Book To Read For Beginners In Genetic Algorithms. Can Be Improved By Including More Implementation Details.
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am 14. August 1998
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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am 17. Oktober 1998
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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am 21. Februar 2000
This book is brief and to the point. You won't find here pages of source code that you could have easily ftp'd yourself. What you will find is solid theory in a mere 224 pages. This is the quickest and best way to get up to speed on GA's there is. Which is why it is a standard textbook in the field.
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am 27. Mai 1999
Good Book To Read For Beginners In Genetic Algorithms. Can Be Improved By Including More Implementation Details.
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