Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Book{Miller:CGP,
  editor =       "Julian F. Miller",
  title =        "Cartesian Genetic Programming",
  publisher =    "Springer",
  year =         "2011",
  series =       "Natural Computing Series",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming, (CGP), Directed Graphs, Electronic
                 Circuits, Evolutionary Art, Evolutionary Computing
                 (EC), Evolvable Hardware (EHW), Image Processing,
                 Modular (Embedded) CGP, Natural Computing,
                 Self-modifying CGP",
  isbn13 =       "978-3-642-17309-7",
  URL =          "http://www.springer.com/computer/theoretical+computer+science/book/978-3-642-17309-7",
  DOI =          "doi:10.1007/978-3-642-17310-3",
  size =         "344 pages",
  abstract =     "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 to 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 use a highly efficient form
                 of genetic programming.",
}

Genetic Programming entries for Julian F Miller

Citations