Genetic Programming Iv

Author : John R. Koza,Martin A. Keane,Matthew J. Streeter,William Mydlowec,Jessen Yu,Guido Lanza
Publisher : Springer Science & Business Media
Page : 626 pages
File Size : 45,8 Mb
Release : 2005-03-21
Category : Computers
ISBN : 0387250670

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Genetic Programming IV by John R. Koza,Martin A. Keane,Matthew J. Streeter,William Mydlowec,Jessen Yu,Guido Lanza Pdf

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

Author : Rick Riolo,Terence Soule,Bill Worzel
Publisher : Springer Science & Business Media
Page : 349 pages
File Size : 43,5 Mb
Release : 2007-07-03
Category : Computers
ISBN : 9780387496504

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Genetic Programming Theory and Practice IV by Rick Riolo,Terence Soule,Bill Worzel Pdf

Genetic Programming Theory and Practice IV was developed from the fourth workshop at the University of Michigan’s Center for the Study of Complex Systems. The workshop was convened in May 2006 to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application.

Author : John R. Koza,Martin A. Keane,Matthew J. Streeter,William Mydlowec,Jessen Yu,Guido Lanza
Publisher : Springer Science & Business Media
Page : 607 pages
File Size : 44,5 Mb
Release : 2005-09-14
Category : Computers
ISBN : 9780387264172

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Genetic Programming IV by John R. Koza,Martin A. Keane,Matthew J. Streeter,William Mydlowec,Jessen Yu,Guido Lanza Pdf

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

Author : John R. McDonnell,Robert G. Reynolds
Publisher : MIT Press
Page : 840 pages
File Size : 47,9 Mb
Release : 1995
Category : Evolutionary programming (Computer science)
ISBN : 0262133172

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Evolutionary Programming IV by John R. McDonnell,Robert G. Reynolds Pdf

Author : John R. Koza
Publisher : Morgan Kaufmann
Page : 1516 pages
File Size : 44,8 Mb
Release : 1999
Category : Computers
ISBN : 1558605436

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Genetic Programming III by John R. Koza Pdf

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.

Author : Michael O'Neill,Conor Ryan
Publisher : Springer Science & Business Media
Page : 157 pages
File Size : 42,7 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461504474

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Grammatical Evolution by Michael O'Neill,Conor Ryan Pdf

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.

Author : Rick Riolo,Terence Soule,Bill Worzel
Publisher : Springer
Page : 338 pages
File Size : 50,7 Mb
Release : 2007-03-14
Category : Computers
ISBN : 0387333754

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Genetic Programming Theory and Practice IV by Rick Riolo,Terence Soule,Bill Worzel Pdf

Genetic Programming Theory and Practice IV was developed from the fourth workshop at the University of Michigan’s Center for the Study of Complex Systems. The workshop was convened in May 2006 to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application.

Author : Anonim
Publisher : Lulu.com
Page : 252 pages
File Size : 50,7 Mb
Release : 2008
Category : Computers
ISBN : 9781409200734

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A Field Guide to Genetic Programming by Anonim Pdf

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.

Author : John R. Koza
Publisher : MIT Press
Page : 856 pages
File Size : 41,8 Mb
Release : 1992
Category : Computers
ISBN : 0262111705

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Genetic Programming by John R. Koza Pdf

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.

Author : Kenneth E. Kinnear (Jr.),Peter J. Angeline
Publisher : MIT Press
Page : 544 pages
File Size : 40,9 Mb
Release : 1994
Category : Computers
ISBN : 0262111888

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Advances in Genetic Programming by Kenneth E. Kinnear (Jr.),Peter J. Angeline Pdf

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.

Author : Fangfang Zhang,Su Nguyen,Yi Mei,Mengjie Zhang
Publisher : Springer Nature
Page : 357 pages
File Size : 40,9 Mb
Release : 2021-11-12
Category : Computers
ISBN : 9789811648595

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Genetic Programming for Production Scheduling by Fangfang Zhang,Su Nguyen,Yi Mei,Mengjie Zhang Pdf

This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling. The book is divided into six parts. In Part I, it provides an introduction to production scheduling, existing solution methods, and the GP approach to production scheduling. Characteristics of production environments, problem formulations, an abstract GP framework for production scheduling, and evaluation criteria are also presented. Part II shows various ways that GP can be employed to solve static production scheduling problems and their connections with conventional operation research methods. In turn, Part III shows how to design GP algorithms for dynamic production scheduling problems and describes advanced techniques for enhancing GP’s performance, including feature selection, surrogate modeling, and specialized genetic operators. In Part IV, the book addresses how to use heuristics to deal with multiple, potentially conflicting objectives in production scheduling problems, and presents an advanced multi-objective approach with cooperative coevolution techniques or multi-tree representations. Part V demonstrates how to use multitask learning techniques in the hyper-heuristics space for production scheduling. It also shows how surrogate techniques and assisted task selection strategies can benefit multitask learning with GP for learning heuristics in the context of production scheduling. Part VI rounds out the text with an outlook on the future. Given its scope, the book benefits scientists, engineers, researchers, practitioners, postgraduates, and undergraduates in the areas of machine learning, artificial intelligence, evolutionary computation, operations research, and industrial engineering.

Author : John R. Koza
Publisher : Bradford Books
Page : 746 pages
File Size : 40,8 Mb
Release : 1994
Category : Computers
ISBN : 0262111896

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Genetic Programming II by John R. Koza Pdf

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.

Author : Stefano Cagnoni
Publisher : Hindawi Publishing Corporation
Page : 473 pages
File Size : 50,6 Mb
Release : 2008
Category : Computer vision
ISBN : 9789774540011

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Genetic and Evolutionary Computation for Image Processing and Analysis by Stefano Cagnoni Pdf

Author : Jason Brownlee
Publisher : Jason Brownlee
Page : 437 pages
File Size : 49,5 Mb
Release : 2011
Category : Computers
ISBN : 9781446785065

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Clever Algorithms by Jason Brownlee Pdf

This book provides a handbook of algorithmic recipes from the fields of Metaheuristics, Biologically Inspired Computation and Computational Intelligence that have been described in a complete, consistent, and centralized manner. These standardized descriptions were carefully designed to be accessible, usable, and understandable. Most of the algorithms described in this book were originally inspired by biological and natural systems, such as the adaptive capabilities of genetic evolution and the acquired immune system, and the foraging behaviors of birds, bees, ants and bacteria. An encyclopedic algorithm reference, this book is intended for research scientists, engineers, students, and interested amateurs. Each algorithm description provides a working code example in the Ruby Programming Language.

Author : Melanie Mitchell
Publisher : MIT Press
Page : 226 pages
File Size : 40,5 Mb
Release : 1998-03-02
Category : Computers
ISBN : 0262631857

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An Introduction to Genetic Algorithms by Melanie Mitchell Pdf

Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.