Articles liés à Cartesian Genetic Programming

Cartesian Genetic Programming - Couverture rigide

 
9783642173097: Cartesian Genetic Programming

Synopsis

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.

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À propos de l'auteur

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.

À propos de la quatrième de couverture

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.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.