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Genetic algorithms are used in science and engineering for problem solving and as computational models. This brief introduction enables readers to implement and experiment with genetic algorithms on their own. The descriptions of applications and modeling projects stretch beyond the boundaries of computer science to include systems theory, game theory, biology, ecology, and population genetics. 20 illustrations.
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.
A.E. Eiben, J.E. Smith
The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.
John R. Koza
Genetic programming may be more powerful than neural networks and other machinelearning techniques, able to solve problems in a wider range of disciplines. In this ground-breakingbook, John Koza shows how this remarkable paradigm works and provides substantial empirical evidencethat solutions to a great variety of problems from many different fields can be found by geneticallybreeding populations of computer programs. Genetic Programming contains a great many worked examplesand includes a sample computer code that will allow readers to run their own programs.In gettingcomputers to solve problems without being explicitly programmed, Koza stresses two points: thatseemingly different problems from a variety of fields can be reformulated as problems of programinduction, and that the recently developed genetic programming paradigm provides a way to search thespace of possible computer programs for a highly fit individual computer program to solve theproblems of program induction. Good programs are found by evolving them in a computer against afitness measure instead of by sitting down and writing them.John R. Koza is Consulting AssociateProfessor in the Computer Science Department at Stanford University.
Some of the most startling achievements in the use of computers to automate design are being accomplished by the use of evolutionary search algorithms to evolve designs. Evolutionary Design By Computers provides a showcase of the best and most original work of the leading international experts in Evolutionary Computation, Engineering Design, Computer Art, and Artificial Life. By bringing together the highest achievers in these fields for the first time, including a foreword by Richard Dawkins, this book provides the definitive coverage of significant developments in Evolutionary Design. This book explores related sub-areas of Evolutionary Design, including: * design optimization * creative design * the creation of art * artificial life. It shows for the first time how techniques in each area overlap, and promotes the cross-fertilization of ideas and methods. A CD-ROM is included with the book, providing the reader with hands-on activities, evolved images, animations, and source-code related to the text. Evolutionary Design By Computers will be an essential resource for researchers in academia and industry.