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Genetic Programming: An Introduction (The Morgan Kaufmann Series in Artificial Intelligence) Hardcover – December 15, 1997

ISBN-13: 978-1558605107 ISBN-10: 155860510X Edition: 1st

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Product Details

  • Series: The Morgan Kaufmann Series in Artificial Intelligence
  • Hardcover: 512 pages
  • Publisher: Morgan Kaufmann; 1 edition (December 15, 1997)
  • Language: English
  • ISBN-10: 155860510X
  • ISBN-13: 978-1558605107
  • Product Dimensions: 7.6 x 1.2 x 9.6 inches
  • Shipping Weight: 2.2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (10 customer reviews)
  • Amazon Best Sellers Rank: #1,119,964 in Books (See Top 100 in Books)

Editorial Reviews

Amazon.com Review

Imagine a world in which computers program other computers based on strategies borrowed from biology and natural selection. Genetic Programming: An Introduction explores fascinating possibilities like these in a thriving area of computer-science research. This research-quality book is for anyone who wants to see what genetic programming is and what it can offer the future of computing.

This text begins by situating genetic programming in terms of the history of computing and machine learning. Early sections show the links between Darwinism, molecular biology, and genetic programming. (Genetic programming uses the strategy of natural selection by solving a problem in successive iterations, which produces the "fittest" solution, much like new species evolve in the natural world.)

The authors present a lot of molecular-biology background since it is central to the genetic-programming project. (There are interesting parallels here. Just as our DNA contains inert information, programs developed using genetic algorithms usually contain many "extra" instructions, too--which often leads to bloated, though effective, code in the final product.) Even though this is extremely technical material, the authors do manage to engage the reader in the imaginative leap from Darwin and DNA to computers and the world of genetic programming.

Later chapters define what genetic programming is and what strategies it uses to let computers program themselves. The authors also examine the state of the art of genetic programming and define what problems need to be solved before it can be widely adopted. The amount of research in this section will mostly benefit specialists in the genetic-programming field.

A later chapter on applications that use genetic programming offers dozens of papers, with applications of this approach from a wide variety of fields, including biology, industry, and computers (and some impressive technologies such as robotics and data mining). Though the authors exaggerate somewhat on how "real world" these applications are, it's clear that genetic programming will continue to improve and find its way into more areas of computing--with even more productive results. Though coding by humans is safe for the foreseeable future, genetic programming offers an appealing alternative to some kinds of problems. --Richard V. Dragan

Review

"[The authors] have performed a remarkable double service with this excellent book on genetic programming. First, they give an up-to-date view of the rapidly growing field of automatic creation of computer programs by means of evolution and, second, they bring together their own innovative and formidable work on evolution of assembly language machine code and linear genomes."
--John R. Koza

Customer Reviews

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Most Helpful Customer Reviews

13 of 14 people found the following review helpful By Paul Zimmons on November 18, 2000
Format: Hardcover
This book is a great introduction to genetic programming and should be a model for textbook authors in other fields. Knowing little about genetic programming to begin with, this book guides the reader through the various topics and problems associated with genetic programming in a very logical and understandable way. Highly recommended! I wish more technical books were like this!
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32 of 39 people found the following review helpful By fdf on May 2, 1998
Format: Hardcover
I am one of the authors, so I will let others do the reviewing. We have spent some time trying to get Amazon.com to remove the "editor" title from Dr. Banzhaf's name because this is NOT an edited volume. It is an entirely original work.
Alas, to no avail.
We spent three years on this book and are very pleased with the results. The reactions we have received from the professionals in the GP community have been much more than we had hoped for. We hope you enjoy it.
Frank Francone
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11 of 12 people found the following review helpful By Steven B. on January 28, 2002
Format: Hardcover Verified Purchase
We all know that kind of books where the author likes to show how much he knows making things intentionally complex....well...this is the opposite side of the spectrum.
The book is very complete and detailed yet easy to read, even after a day of work.
The first part of the book contains introductory information on background areas like probability, biology and computer science as a general discipline.
Getting into the topic, it clarifies some of the differences between evolutionary systems and genetic algorithms and shows how all this contributes to the theory of genetic programming and the evolution of computer programs.
It explains how things are done with different types of individuals (tree, linear, graph, etc) and gives valuable insight about the implementation process.
Although you may need other sources for formal treatment of some topics, this book is a very good acquisition.
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11 of 12 people found the following review helpful By A Customer on May 10, 2003
Format: Hardcover
This book is good for getting a general view of genetic programming. Nevertheless, I think it neglects many details. For example, it is very hard to from the book how a simple selection strategy (tournament selection) works in practice.
I do not think this book is useful for someone intending to code a genetic programming algorithm.
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10 of 11 people found the following review helpful By A Customer on June 23, 1998
Format: Hardcover
It may be the rich subject matter, but this is the first time I've been happy to pay this much for a textbook. It's also the first textbook I've ever actually read through.
It's a well written introduction to a very cool field of study. Now I wish I had gone straight into computer science after I graduated biology in 1993. Even though I'm not doing any work with GP or machine learning, this book lets me feel like an insider. Who knows, maybe it'll mark the start of a new career.
I particularly liked the fact that the content is all very current and very relevant (for 1998). The book provides a good starting point for getting into the scientific papers.
Anyone coming from first year biology or computer science should have no trouble picking up on the major themes here.
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