Genetic Programming IV: Routine Human-Competitive Machine Intelligence [Hardcover]

John R. Koza (Author), Martin A. Keane (Author), Matthew J. Streeter (Author), William Mydlowec (Author), Jessen Yu (Author), Guido Lanza (Author)

Book Description

ISBN-10: 1402074468 | ISBN-13: 978-1402074462 | Publication Date: July 2003

Genetic Programming IV: Routine Human-Competitive Machine Intelligence presents the application of GP to a wide variety of problems involving automated synthesis of controllers, circuits, antennas, genetic networks, and metabolic pathways. The book describes fifteen instances where GP has created an entity that either infringes or duplicates the functionality of a previously patented 20th-century invention, six instances where it has done the same with respect to post-2000 patented inventions, two instances where GP has created a patentable new invention, and thirteen other human-competitive results. The book additionally establishes:

GP now delivers routine human-competitive machine intelligence

GP is an automated invention machine

GP can create general solutions to problems in the form of parameterized topologies

GP has delivered qualitatively more substantial results in synchrony with the relentless iteration of Moore's Law

Editorial Reviews

Review

`Genetic Programming IV: Routine Human-Competitive Machine Intelligence, demonstrates the everyday solution of such `holy grail' problems as the automatic synthesis of analog circuits, the design of automatic controllers, and the automated programming of computers. To specialists in any of the fields covered by this book's sample problem areas, I say read this book and discover the computer-augmented inventions that are your destiny. To remaining skeptics who doubt the inventive competence of genetics and evolution, I say read this book and change your mind or risk the strong possibility that your doubts will soon cause you significant intellectual embarrassment.'
David E. Goldberg, University of Illinois
`The research reported in this book is a tour de force. For the first time since the idea was bandied about in the 1940s and the early 1950s, we have a set of examples of human-competitive automatic programming.'
John H. Holland, University of Michigan
`John Koza and his colleagues have done remarkable work in advancing the development of genetic programming and applying this to practical problems such as electric circuit design and control system design. I strongly recommend it.'
Bernard Widrow, Electrical Engineering Dept., Stanford University
`John Koza's genetic programming approach to machine discovery can invent solutions to more complex specifications than any other I have seen.'
John McCarthy, Computer Science Dept., Stanford University

Product Details

• Hardcover: 624 pages
• Publisher: Springer (July 2003)
• Language: English
• ISBN-10: 1402074468
• ISBN-13: 978-1402074462
• Product Dimensions: 8.9 x 7 x 1.4 inches
• Shipping Weight: 2.2 pounds
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #1,638,836 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

22 of 23 people found the following review helpful:

5.0 out of 5 stars Gp here we Go, September 27, 2004

By 

Martin Arumemi-ikhide - See all my reviews
(REAL NAME)   

This review is from: Genetic Programming IV: Routine Human-Competitive Machine Intelligence (Hardcover)

Since using evolutionary algorithms for my work, it is easy to see how many of the current EAs can be used to solve or tackle various real world problems. But what Koza does once again is to argue the case that GP is more than just an optimization algorithm but instead an algorithm that tries to show what AI should do and how user and AI should interact to solve a problem. Once again numerous examples are given, with detail on how problems are laid out so as to get the best results from the GP. Koza shows that with well thought out planning GP's can be applied to all sorts of fields.
In one of the chapters he presents the characteristics a problem should have for GP to be applicable.
All-round Great work, my advice get all his books and digest how he approaches various problems with GP. This example format Koza uses is far more useful than talking about what GP is and its theory. Though for a good intro into Evolutionary Algorithms including GP get either Foundations of Genetic Programming or an Introduction to Genetic Programming. An all round good intro is Introduction to Evolutionary Computing.