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Genetic Programming: On the Programming of Computers by Means of Natural Selection

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In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic Programming contains a great many worked examples and includes a sample computer code that will allow readers to run their own programs.In getting computers to solve problems without being explicitly programmed, Koza stresses two points: that seemingly different problems from a variety of fields can be reformulated as problems of program induction, and that the recently developed genetic programming paradigm provides a way to search the space of possible computer programs for a highly fit individual computer program to solve the problems of program induction. Good programs are found by evolving them in a computer against a fitness measure instead of by sitting down and writing them.


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In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic Programming contains a great many worked examples and includes a sample computer code that will allow readers to run their own programs.In getting computers to solve problems without being explicitly programmed, Koza stresses two points: that seemingly different problems from a variety of fields can be reformulated as problems of program induction, and that the recently developed genetic programming paradigm provides a way to search the space of possible computer programs for a highly fit individual computer program to solve the problems of program induction. Good programs are found by evolving them in a computer against a fitness measure instead of by sitting down and writing them.

30 review for Genetic Programming: On the Programming of Computers by Means of Natural Selection

  1. 4 out of 5

    Costin Manda

    Oh, the monster of a book! If you want to learn to do genetic programming, then this is the book for you. If you need an interesting presentation of what genetic programming is, then this book is way too heavy. Let's start with the beginning. Genetic Programming: On the Programming of Computers by Means of Natural Selection (Complex Adaptive Systems) is a scientific book written by John R. Koza to explain why, how and what to do to make your computer find solutions to problems by using natural se Oh, the monster of a book! If you want to learn to do genetic programming, then this is the book for you. If you need an interesting presentation of what genetic programming is, then this book is way too heavy. Let's start with the beginning. Genetic Programming: On the Programming of Computers by Means of Natural Selection (Complex Adaptive Systems) is a scientific book written by John R. Koza to explain why, how and what to do to make your computer find solutions to problems by using natural selection algorithms to automatically create programs to solve them. This is not a new field and a lot of research has been done in it, but this book takes it almost to the level of encyclopedic knowledge. First, Koza submits the idea that genetic programming can be used in most problems where computers are been used. That's a bold claim, but he proceeds on demonstrating it. He takes problem classes, provides code to create the programs that solve them, shows results and statistical analysis on the results and explains what the algorithm did to create said program at specific iterations. That's a lot to take in. If you are working on a program and you are using the book, you are more likely to find it extremely useful, both as a source for information and as a reference that can always be consulted. However, if you are a casual reader like myself, reading all that code and statistical analysis in the subway can be difficult. And it's a lot of book, too. So, after some consideration, realizing that I have no current project on which to apply the knowledge within the book, I've decided to stop reading it. I got to about a quarter of it, so I can safely say that it is a very thorough and well written book. You just have to need it in a certain way.

  2. 4 out of 5

    B

  3. 4 out of 5

    Greg

  4. 5 out of 5

    Goodguy Greg

  5. 4 out of 5

    Gregor Erbach

  6. 5 out of 5

    Paul

  7. 5 out of 5

    Marius Fersigan

  8. 4 out of 5

    Gregory

  9. 5 out of 5

    Peter

  10. 5 out of 5

    Ashia

  11. 5 out of 5

    Marcin

  12. 4 out of 5

    Subhajit Das

  13. 5 out of 5

    Gustavo Gonzalez

  14. 4 out of 5

    Tom

  15. 4 out of 5

    Bill White

  16. 4 out of 5

    Dan Litwiller

  17. 4 out of 5

    Chris Green

  18. 5 out of 5

    Wasan

    It is the best book on GP

  19. 5 out of 5

    Paul

  20. 4 out of 5

    Facedeer

  21. 5 out of 5

    Hakan Kjellerstrand

  22. 5 out of 5

    Richard

  23. 4 out of 5

    Lucky

  24. 5 out of 5

    Lieb

  25. 5 out of 5

    Peet Badenhorst

  26. 5 out of 5

    Dan McKinley

  27. 4 out of 5

    Jovany Agathe

  28. 5 out of 5

    Trinity

  29. 5 out of 5

    Paul Tupciauskas

  30. 5 out of 5

    Michael

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