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Cartesian Genetic Programming / edited by Julian F. Miller.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Miller, Julian F., editor.
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
Natural computing series 1619-7127
Natural Computing Series, 1619-7127
Language:
English
Subjects (All):
Computers.
Electrical engineering.
Artificial intelligence.
Computer-aided engineering.
Application software.
Theory of Computation.
Electrical Engineering.
Artificial Intelligence.
Computer-Aided Engineering (CAD, CAE) and Design.
Computer Appl. in Arts and Humanities.
Local Subjects:
Theory of Computation.
Electrical Engineering.
Artificial Intelligence.
Computer-Aided Engineering (CAD, CAE) and Design.
Computer Appl. in Arts and Humanities.
Physical Description:
1 online resource (XXII, 346 pages).
Edition:
First edition 2011.
Contained In:
Springer eBooks
Place of Publication:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011.
System Details:
text file PDF
Summary:
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. .
Contents:
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.
Other Format:
Printed edition:
ISBN:
978-3-642-17310-3
9783642173103
Access Restriction:
Restricted for use by site license.

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