title: Meta-Genetic Programming: Co-evolving the Operators of Variation
creator: Edmonds, Bruce
subject: Theoretical Biology
subject: Artificial Intelligence
subject: Machine Learning
description: The standard Genetic Programming approach is augmented by co-evolving the genetic operators. To do this the operators are coded as trees of indefinite length. In order for this technique to work, the language that the operators are defined in must be such that it preserves the variation in the base population. This technique can varied by adding further populations of operators and changing which populations act as operators for others, including itself, thus to provide a framework for a whole set of augmented GP techniques. The technique is tested on the parity problem. The pros and cons of the technique are discussed.
publisher: the Scientific and Technical Research Council of Turkey
contributor: Akman, Varol
date: 2001
type: Journal (Paginated)
type: NonPeerReviewed
format: application/postscript
identifier: http://cogprints.org/1776/1/mgpA4.ps
format: application/pdf
identifier: http://cogprints.org/1776/5/mgp.pdf
identifier:   Edmonds, Bruce  (2001) Meta-Genetic Programming: Co-evolving the Operators of Variation.  [Journal (Paginated)]     
relation: http://cogprints.org/1776/