# A Less Destructive, Context-aware Crossover Operator for GP

Created by W.Langdon from gp-bibliography.bib Revision:1.4448

@InProceedings{eurogp06:MajeedRyan,
author =       "Hammad Majeed and Conor Ryan",
title =        "A Less Destructive, Context-aware Crossover Operator
for {GP}",
editor =       "Pierre Collet and Marco Tomassini and Marc Ebner and
Steven Gustafson and Anik\'o Ek\'art",
booktitle =    "Proceedings of the 9th European Conference on Genetic
Programming",
publisher =    "Springer",
series =       "Lecture Notes in Computer Science",
volume =       "3905",
year =         "2006",
month =        "10 - 12 " # apr,
organisation = "EvoNet",
keywords =     "genetic algorithms, genetic programming, steepest
ascent crossover hill climbing",
ISBN =         "3-540-33143-3",
pages =        "36--48",
DOI =          "doi:10.1007/11729976_4",
bibsource =    "DBLP, http://dblp.uni-trier.de",
abstract =     "Standard GP crossover is widely accepted as being a
largely {\em destructive} operator, creating many poor
offspring in the search for better ones. One of the
major reasons for its destructiveness is its disrespect
for the context of swapped subtrees in their respective
parent trees when creating offspring. At times, this
hampers GP's performance considerably, and results in
populations with {\em low} average fitness values.

Many attempts have been made to make it a more
constructive crossover, mostly by preserving the
context of the selected subtree in the offspring.
Although successful at preserving context, none of
these methods provide the opportunity to discover new
and better contexts for exchanged subtrees.

We introduce a context-aware crossover operator which
operates by identifying all possible contexts for a
subtree, and evaluating each of them. The context that
produces the highest fitness is used to create a child
which is then passed into the next generation.

We have tested its performance on many benchmark
problems. It has shown better results than the standard
GP crossover operator, using either the same number or
fewer individual evaluations. Furthermore, the average
fitness of populations using this scheme improves
considerably, and programs produced in this way are
much smaller than those produced using standard
crossover.",
notes =        "Part of \cite{collet:2006:GP} EuroGP'2006 held in
conjunction with EvoCOP2006 and
EvoWorkshops2006.

Variation in operator frequencies from beginning to end
of GP run.",
}



Genetic Programming entries for Hammad Majeed Conor Ryan

Citations