Problem Decomposition in Cartesian Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InCollection{Walker:2011:CGP,
-
author = "James Alfred Walker and Julian F. Miller and
Paul Kaufmann and Marco Platzner",
-
title = "Problem Decomposition in Cartesian Genetic
Programming",
-
booktitle = "Cartesian Genetic Programming",
-
publisher = "Springer",
-
editor = "Julian F. Miller",
-
year = "2011",
-
series = "Natural Computing Series",
-
chapter = "3",
-
pages = "35--99",
-
keywords = "genetic algorithms, genetic programming, Cartesian
Genetic Programming",
-
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_3",
-
abstract = "Scalability has become a major issue and a hot topic
of research for the GP community, as researchers are
moving on to investigate more complex problems.
Throughout nature and conventional human design
principles, modular structures are extensively used to
tackle complex problems by decomposing them into
smaller, simpler subproblems, which can be
independently solved. Modularity is defined as the
degree to which an entity can be represented in terms
of smaller functional blocks. These smaller functional
blocks are known as modules. In this chapter, a new
approach called Embedded CGP (ECGP), is described that
is capable of dynamically acquiring, evolving, and
reusing modules to exploit modularity. Alternative
approaches for acquiring modules within ECGP are also
discussed before describing Modular CGP (MCGP), an
enhancement to ECGP that allows the use of nested
modules to see if further performance improvements are
possible. Finally, an approach that uses the concept of
multiple chromosomes in order to allow CGP and ECGP to
exploit modularity through compartmentalisation is
described.",
-
notes = "part of \cite{Miller:CGP}",
- }
Genetic Programming entries for
James Alfred Walker
Julian F Miller
Paul Kaufmann
Marco Platzner
Citations