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Genetic Programming: An Introduction (The Morgan Kaufmann Series in Artificial Intelligence)
 
 
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Genetic Programming: An Introduction (The Morgan Kaufmann Series in Artificial Intelligence) (Hardcover)

~ Wolfgang Banzhaf (Author), Peter Nordin (Author), Robert E. Keller (Author), Frank D. Francone (Author) "Automatic programming will be one of the most important areas of computer science research over the next twenty years..." (more)
Key Phrases: brood recombination, intron equivalents, biological introns, New York, The Foundation, Dick Tracy (more...)
4.4 out of 5 stars  See all reviews (10 customer reviews)

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Genetic Programming: An Introduction (The Morgan Kaufmann Series in Artificial Intelligence) + A Field Guide to Genetic Programming + Foundations of Genetic Programming
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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 -- Review

Product Details

  • Hardcover: 512 pages
  • Publisher: Morgan Kaufmann; 1st edition (December 15, 1997)
  • Language: English
  • ISBN-10: 155860510X
  • ISBN-13: 978-1558605107
  • Product Dimensions: 9.3 x 7.4 x 1.2 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.com Sales Rank: #718,833 in Books (See Bestsellers in Books)

    Popular in these categories: (What's this?)

    #15 in  Books > Computers & Internet > Programming > Algorithms > Genetic
    #83 in  Books > Computers & Internet > Computer Science > Artificial Intelligence > Machine Learning

Inside This Book (learn more)
First Sentence:
Automatic programming will be one of the most important areas of computer science research over the next twenty years. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
brood recombination, intron equivalents, biological introns, improving crossover, destructive crossover, other machine learning systems, trait mining, chicken crossover, replicase experiments, intron growth, macromutation operator, neutral crossover, biological crossover, parsimony pressure, defined introns, fitness cases, effective fitness, using genetic programming, indexed memory, genetic programming system, homologous exchange, variable length structures, subtree crossover, absolute complexity, homologous crossover
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, The Foundation, Dick Tracy, Morgan Kaufmann, Further Reading, Implementations Using, Flavors of Evolutionary Algorithms, New Directions, San Francisco, San Mateo, Empirical Evidence of Crossover Effects, Executable Program Structures, Implementations With Arrays, Parallel Problem Solving, Representing the Problem, Some Necessary Data Structures, Consider Figure, John Wiley, Other Genomes, Oxford University Press, The Effects of Introns, The Emergence of Introns, The Primitives of Genetic Programs, Lecture Notes, Minimalist Evolution
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What Do Customers Ultimately Buy After Viewing This Item?

Genetic Programming: An Introduction (The Morgan Kaufmann Series in Artificial Intelligence)
49% buy the item featured on this page:
Genetic Programming: An Introduction (The Morgan Kaufmann Series in Artificial Intelligence) 4.4 out of 5 stars (10)
$71.27
A Field Guide to Genetic Programming
15% buy
A Field Guide to Genetic Programming 4.6 out of 5 stars (5)
$13.95
Introduction to Evolutionary Computing (Natural Computing Series)
14% buy
Introduction to Evolutionary Computing (Natural Computing Series) 4.5 out of 5 stars (6)
An Introduction to Genetic Algorithms (Complex Adaptive Systems)
12% buy
An Introduction to Genetic Algorithms (Complex Adaptive Systems) 4.2 out of 5 stars (17)
$19.74

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10 Reviews
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Average Customer Review
4.4 out of 5 stars (10 customer reviews)
 
 
 
 
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Most Helpful Customer Reviews

 
31 of 36 people found the following review helpful:
5.0 out of 5 stars Great Book. It is an original book -- not edited., May 2, 1998
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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12 of 12 people found the following review helpful:
5.0 out of 5 stars A great introduction!, November 18, 2000
By Paul Zimmons (Chapel Hill, North Carolina United States) - See all my reviews
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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10 of 11 people found the following review helpful:
5.0 out of 5 stars Excellent, comprehensive and easy to read., January 28, 2002
Amazon Verified Purchase(What's this?)
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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Most Recent Customer Reviews

1.0 out of 5 stars Almost a popularization.
I have no idea how this is marketed as a college level text on the subject. It is just a 'high level' text suitable for non programmers interested in learning some of the... Read more
Published 14 months ago by Justin Van Winkle

5.0 out of 5 stars Fantastic introduction
It's rare to find an advanced computer science textbook that's both so engaging and so informative. I've only read the first seven chapters so far, but when I sat down to write... Read more
Published 21 months ago by Christian J. Convey

3.0 out of 5 stars Good as an overall, not for the details
This book is good for getting a general view of genetic programming. Nevertheless, I think it neglects many details. Read more
Published on May 11, 2003

5.0 out of 5 stars terrific textbook
I skimmed the Koza books (GP: I & II) and this one at the store. Using the layout, chapter names, and the introductory chapters as my guide, I decided to buy this book to... Read more
Published on April 17, 2003 by M. Joya

5.0 out of 5 stars Excellent Book on Genetic Programming
Genetic Programming is an exciting field, and as the desktop computers become more powerful, more applications are occuring. Read more
Published on January 19, 2000 by Larry M. Deschaine, PE

5.0 out of 5 stars This book is well written and comprehensive.
The authors are to be congratulated on presenting a volume which:

- factually and clearly elucidates the relationship between GP and machine learning, or biology. Read more

Published on September 4, 1998 by Una-May O'Reilly (unamay@ai.mi...

5.0 out of 5 stars Excellent introduction to Genetic Programming
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. Read more
Published on June 23, 1998

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