Cartesian Genetic Programming

Häftad, Engelska, 2013

1 369 kr

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Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype–phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences. This book contains chapters written by the leading figures in the development and application of CGP, and it will be essential reading for researchers in genetic programming and for engineers and scientists solving applications using these techniques. It will also be useful for advanced undergraduates and postgraduates seeking to understand and utilize a highly efficient form of genetic programming.

Produktinformation

Utgivningsdatum2013-11-27
Mått155 x 235 x 20 mm
Vikt557 g
FormatHäftad
SpråkEngelska
SerieNatural Computing Series
Antal sidor346
Upplaga2011
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9783642269981

Tillhör följande kategorier

Tillämpad datateknik inom Data och IT
Systemvetenskap och AI inom Data och IT
Energiteknik inom Naturvetenskap och teknik
Artificiell intelligens inom Data och IT
CAD-program inom Data och IT

The author has a degree in physics and a Ph.D. in nonlinear mathematics. He worked at Napier University and the University of Birmingham University, and he's now a lecturer in the Dept. of Electronics at The University of York. He has chaired many international conferences and workshops in genetic programming and evolvable hardware; he cofounded one of the key evolutionary computing journals; he has authored over 150 publications in the area; and he is the coinventor of the Cartesian GP method.

Introduction.- Cartesian Genetic Programming.- Modular Cartesian Genetic Programming.- Self-modifying Cartesian Genetic Programming.- Evolution of Electronic Circuits.- Image Processing.- Developmental Approaches.- Artificial Neural Approaches.- Medical Applications.- Hardware Acceleration.- Control Applications.- Evolutionary Art.- Future Directions.- App. A, A Bibliography of CGP Papers.- App. B, CGP Software.

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