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Computer Science - Theoretical Computer Science | Cartesian Genetic Programming

Cartesian Genetic Programming

Miller, Julian F. (Ed.)

2011, XXII, 346 p.

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  • Covers Cartesian Genetic Programming (CGP), a highly effective and increasingly popular form of genetic programming
  • Edited by the co-inventor of the method
  • Features contributions by leading researchers in the field

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.

 

Content Level » Research

Keywords » Cartesian Genetic Programming (CGP) - Directed Graphs - Electronic Circuits - Evolutionary Art - Evolutionary Computing (EC) - Evolvable Hardware - Genetic Programming (GP) - Image Processing - Modular (Embedded) CGP - Natural Computing - Self-modifying CGP

Related subjects » Artificial Intelligence - Electronics & Electrical Engineering - Information Systems and Applications - Theoretical Computer Science

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