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 genotypeaphenotype 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.However, it does highlight the problem of selecting a suitable maximum limit for the size of the modules. ... acquisition, evolution and reuse of modules in ECGP causes ECGP to start to outperform CGP for most of the smaller choices for the maximum size limit of the modules. ... The lawnmower problem was first introduced by Koza in his second book  to test the effectiveness of automatically definedanbsp;...
|Title||:||Cartesian Genetic Programming|
|Author||:||Julian F. Miller|
|Publisher||:||Springer Science & Business Media - 2011-09-18|