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An Introduction to Genetic Algorithms PDF, ePub eBook

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30 review

An Introduction to Genetic Algorithms

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An Introduction to Genetic Algorithms PDF, ePub eBook "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, s "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. 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.

30 review for An Introduction to Genetic Algorithms

  1. 4 out of 5

    Richard

    This is an introduction to genetic algorithms with case studies and a literature survey. It's 20 years old, so the survey is like a time capsule from the late 90s (I've no idea how much the GA world has moved on since then). But the introduction part is timeless, the exercises useful, and importantly the book is nice and short.

  2. 5 out of 5

    Alan

    good readable introduction or refresher

  3. 4 out of 5

    Suneel Madhekar

    This is the first book I've read on GAs. The impression that it makes is that the field of Genetic Algorithms is nascent (or at least was, at the time of writing the book). I was hoping for solid insights into various issues related to GAs, like which problems are best suited for a GA based solution, how to design a GA for a given problem, how to choose the various primitives for a GA, and how to select various parameters... However, I could find none of that. All that I saw was heuristics, heur This is the first book I've read on GAs. The impression that it makes is that the field of Genetic Algorithms is nascent (or at least was, at the time of writing the book). I was hoping for solid insights into various issues related to GAs, like which problems are best suited for a GA based solution, how to design a GA for a given problem, how to choose the various primitives for a GA, and how to select various parameters... However, I could find none of that. All that I saw was heuristics, heuristics and more heuristics. I cannot fault the book, for it is the nature of the subject, perhaps. I could see that GAs are a promising area, but complex and not fully understood. I think, a newer book would have more and recent examples.

  4. 4 out of 5

    Simone Scardapane

    Gran bella introduzione agli Algoritmi Genetici, buon bilanciamento fra esempi e teoria (due capitoli ciascuno). Inoltre, ottima parte finale con tutti i riferimenti per maggiori informazioni. (PS: ormai un po' datato.)

  5. 4 out of 5

    James

    A great intro to the subject.

  6. 5 out of 5

    Tim

    Good intro to the topic. Still relevant after all these years, that is commendable.

  7. 4 out of 5

    Heba Mostafa

    selective reading was useful

  8. 4 out of 5

    Owen Lindsell

    The best book around on one of the most fascinating subjects around. Contains everything you need to know to start writing genetic algorithms.

  9. 5 out of 5

    James Drain

    Genetic algorithms are very underwhelming. There should at least be a few captivating (nonbiological) examples, but this book presents very few successes.

  10. 4 out of 5

    Rachel Wheelock

  11. 4 out of 5

    Azeem Lakdawalla

  12. 4 out of 5

    Bernadette Policarpio

  13. 4 out of 5

    Marko Puza

  14. 4 out of 5

    Phelan

  15. 4 out of 5

    HappyEvilSlosh

  16. 5 out of 5

    Bruno Roberto Búrigo

  17. 4 out of 5

    Julian

  18. 5 out of 5

    Patrick Mcknight

  19. 5 out of 5

    Tuomas Salmi

  20. 5 out of 5

    Brent Mashburn

  21. 5 out of 5

    Juk

  22. 5 out of 5

    Derek

  23. 5 out of 5

    Tom

  24. 4 out of 5

    Asomolinos

  25. 5 out of 5

    Andrea

  26. 5 out of 5

    ne

  27. 5 out of 5

    Rad

  28. 4 out of 5

    Gerall Kahla

  29. 4 out of 5

    Brian Starke

  30. 5 out of 5

    Fabio Ticconi

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