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Genetic Programming

Genetic Programming

Genetic programming is an extension of genetic algorithms that allows for refining and improving computer programs to seek solutions in the same way.

John Koza Has Built an Invention Machine – [popsci.com]

Now 62 and an adjunct professor at Stanford University, Koza is the inventor of genetic programming, a revolutionary approach to artificial intelligence (AI) capable of solving complex engineering problems with virtually no human guidance. Koza´s 1,000 networked computers don´t just follow a preordained routine. They create, growing new and unexpected designs out of the most basic code. They are computers that innovate, that find solutions not only equal to but better than the best work of expert humans. His â€invention machine,†as he likes to call it, has even earned a U.S. patent for developing a system to make factories more efficient, one of the first intellectual-property protections ever granted to a nonhuman designer.

Yet as impressive as these creations may be, none are half as significant as the machine´s method: Darwinian evolution, the process of natural selection. Over and over, bits of computer code are, essentially, procreating. And over the course of hundreds or thousands of generations, that code evolves into offspring so well-adapted for its designated job that it is demonstrably superior to anything we can imagine. The age of creative machines has arrived. And its prophet is John Koza.

A Field Guide to Genetic Programming
– [gp-field-guide.org.uk]

About the book

A Field Guide to Genetic Programming (ISBN 978-1-4092-0073-4) is an introduction to genetic programming (GP). GP is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions.

The book is freely downloadable under a Creative Commons license as a PDF and low cost printed copies can be purchased from lulu.com. This web site will be used for information relating to the book, and other pertinent announcements. We also have a discussion group for questions and conversation related to the book.

Evolutionary Computation
Genetic Algorithms
Neural Networks

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