Genetic Programming: On the Programming of Computers by Means of Natural Selection (Complex Adaptive Systems)
Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. Get and download textbook Genetic Programming: On the Programming of Computers by Means of Natural Selection (Complex Adaptive Systems) for free
Springer-Verlag New York Inc. | 2005 | 620 pages | ISBN-13: 9780387250670 | ISBN-10: 0387250670 | You save 15%
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 Genetic Programming new edition
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This book constitutes the refereed proceedings of the 15th European Conference on Genetic Programming, EuroGP 2012, held in Málaga, Spain, in April 2012 co-located with the Evo* 2012 events.
The 18 revised full papers presented together with 5 poster papers were carefully reviewed and selected from 46 submissions. The wide range of topics in this volume reflects the current state of research in the field, including different genres of GP (tree-based, grammar-based, Cartesian), theory, novel operators, and applications.
The 18 revised full papers presented together with 5 poster papers were carefully reviewed and selected from 46 submissions. The wide range of topics in this volume reflects the current state of research in the field, including different genres of GP (tree-based, grammar-based, Cartesian), theory, novel operators, and applications.
Categories: Genetic programming (Computer science). Contributors: James A. Foster - Author. Format: Paperback
Categories: Data mining, Genetic programming (Computer science). Contributors: Man Leung Wong - Author. Format: Hardcover
Categories: Genetic programming (Computer science). Contributors: Michael O'Neill - Author. Format: Paperback
Genetic Programming Textbook
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
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
