- Series: Genetic Programming (Book 5)
- Hardcover: 624 pages
- Publisher: Springer; 1st ed. 2003. Corr. 2nd printing edition (July 31, 2003)
- Language: English
- ISBN-10: 1402074468
- ISBN-13: 978-1402074462
- Product Dimensions: 6.5 x 1.2 x 9.5 inches
- Shipping Weight: 2.2 pounds
- Average Customer Review: 4 customer reviews
- Amazon Best Sellers Rank: #3,766,268 in Books (See Top 100 in Books)
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Genetic Programming IV: Routine Human-Competitive Machine Intelligence 1st ed. 2003. Corr. 2nd printing Edition
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`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
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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.
Table of Contents
1 Introduction 1
2 Background on genetic programming 29
3 Automatic synthesis of controllers 49
4 Automatic synthesis of circuits 129
5 Automatic synthesis of circuit topology, sizing, placement, and routing 175
6 Automatic synthesis of antennas 205
7 Automatic synthesis of genetic networks 221
8 Automatic synthesis of metabolic pathways 229
9 Automatic synthesis of parameterized topologies for controllers 281
10 Automatic synthesis of parameterized topologies for circuits 301
11 Automatic synthesis of parameterized topologies with conditional developmental operators for circuits 341
12 Automatic synthesis of improved tuning rules for PID controllers 367
13 Automatic synthesis of parameterized topologies for improved controllers 387
14 Reinvention of negative feedback 413
15 Automated reinvention of six post-2000 patented circuits 421
16 Problems for which genetic programming may be well suited 483
17 Parallel implementation and computer time 515
18 Historical perspective on Moore's law and the progression of qualitatively more substantial results produced by genetic programming 523
19 Conclusion 529