Cartesian Genetic Programming [electronic resource] /
Miller, Julian F.editor.
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.  .
Description based upon print version of record.
Includes bibliographical references and index.
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.
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.  .
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.
Natural Computing Series