Genetic Programming IV

Genetic Programming IV
Author: John R. Koza
Publisher: Springer Science & Business Media
Total Pages: 626
Release: 2005-03-21
Genre: Computers
ISBN: 9780387250670

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

Genetic Programming IV

Genetic Programming IV
Author: John R. Koza
Publisher: Springer Science & Business Media
Total Pages: 607
Release: 2005-09-14
Genre: Computers
ISBN: 0387264175

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

Genetic Programming IV

Genetic Programming IV
Author: John R. Koza
Publisher: Springer Science & Business Media
Total Pages: 632
Release: 2003-07-31
Genre: Computers
ISBN: 9781402074462

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

Grammatical Evolution

Grammatical Evolution
Author: Michael O'Neill
Publisher: Springer Science & Business Media
Total Pages: 157
Release: 2012-12-06
Genre: Computers
ISBN: 1461504473

Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language provides the first comprehensive introduction to Grammatical Evolution, a novel approach to Genetic Programming that adopts principles from molecular biology in a simple and useful manner, coupled with the use of grammars to specify legal structures in a search. Grammatical Evolution's rich modularity gives a unique flexibility, making it possible to use alternative search strategies - whether evolutionary, deterministic or some other approach - and to even radically change its behavior by merely changing the grammar supplied. This approach to Genetic Programming represents a powerful new weapon in the Machine Learning toolkit that can be applied to a diverse set of problem domains.

A Field Guide to Genetic Programming

A Field Guide to Genetic Programming
Author:
Publisher: Lulu.com
Total Pages: 252
Release: 2008
Genre: Computers
ISBN: 1409200736

Genetic programming (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 high-fitness 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. This unique overview of this exciting technique is written by three of the most active scientists in GP. See www.gp-field-guide.org.uk for more information on the book.

Genetic Programming

Genetic Programming
Author: John R. Koza
Publisher: MIT Press
Total Pages: 856
Release: 1992
Genre: Computers
ISBN: 9780262111706

In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic Programming contains a great many worked examples and includes a sample computer code that will allow readers to run their own programs.In getting computers to solve problems without being explicitly programmed, Koza stresses two points: that seemingly different problems from a variety of fields can be reformulated as problems of program induction, and that the recently developed genetic programming paradigm provides a way to search the space of possible computer programs for a highly fit individual computer program to solve the problems of program induction. Good programs are found by evolving them in a computer against a fitness measure instead of by sitting down and writing them.

Genetic Programming III

Genetic Programming III
Author: John R. Koza
Publisher: Morgan Kaufmann
Total Pages: 1516
Release: 1999
Genre: Computers
ISBN: 9781558605435

Genetic programming (GP) is a method for getting a computer to solve a problem by telling it what needs to be done instead of how to do it. Koza, Bennett, Andre, and Keane present genetically evolved solutions to dozens of problems of design, control, classification, system identification, and computational molecular biology. Among the solutions are 14 results competitive with human-produced results, including 10 rediscoveries of previously patented inventions.

Advances in Genetic Programming

Advances in Genetic Programming
Author: Kenneth E. Kinnear (Jr.)
Publisher: MIT Press
Total Pages: 544
Release: 1994
Genre: Computers
ISBN: 9780262111881

Advances in Genetic Programming reports significant results in improving the power of genetic programming, presenting techniques that can be employed immediately in the solution of complex problems in many areas, including machine learning and the simulation of autonomous behavior. Popular languages such as C and C++ are used in manu of the applications and experiments, illustrating how genetic programming is not restricted to symbolic computing languages such as LISP. Researchers interested in getting started in genetic programming will find information on how to begin, on what public-domain code is available, and on how to become part of the active genetic programming community via electronic mail.

Genetic Algorithm Essentials

Genetic Algorithm Essentials
Author: Oliver Kramer
Publisher: Springer
Total Pages: 94
Release: 2017-01-07
Genre: Technology & Engineering
ISBN: 331952156X

This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand as possible. Further, it avoids a great deal of formalisms and thus opens the subject to a broader audience in comparison to manuscripts overloaded by notations and equations. The book is divided into three parts, the first of which provides an introduction to GAs, starting with basic concepts like evolutionary operators and continuing with an overview of strategies for tuning and controlling parameters. In turn, the second part focuses on solution space variants like multimodal, constrained, and multi-objective solution spaces. Lastly, the third part briefly introduces theoretical tools for GAs, the intersections and hybridizations with machine learning, and highlights selected promising applications.

Genetic Programming II

Genetic Programming II
Author: John R. Koza
Publisher: Bradford Books
Total Pages: 746
Release: 1994
Genre: Computers
ISBN: 9780262111898

Background on genetic algorithms, LISP, and genetic programming. Hierarchical problem-solving. Introduction to automatically defined functions: the two-boxes problem. Problems that straddle the breakeven point for computational effort. Boolean parity functions. Determining the architecture of the program. The lawnmower problem. The bumblebee problem. The increasing benefits of ADFs as problems are scaled up. Finding an impulse response function. Artificial ant on the San Mateo trail. Obstacle-avoiding robot. The minesweeper problem. Automatic discovery of detectors for letter recognition. Flushes and four-of-a-kinds in a pinochle deck. Introduction to biochemistry and molecular biology. Prediction of transmembrane domains in proteins. Prediction of omega loops in proteins. Lookahead version of the transmembrane problem. Evolutionary selection of the architecture of the program. Evolution of primitives and sufficiency. Evolutionary selection of terminals. Evolution of closure. Simultaneous evolution of architecture, primitive functions, terminals, sufficiency, and closure. The role representation and the Lens effect. Default parameters. Computer implementation. Electronic mailing list and public repository.