Traditional genetic programming (GP) randomly combines
subtrees by applying crossover. There is a growing
interest in methods that can control such recombination
operations in order to achieve faster convergence. In
this paper, a new approach is presented for guiding the
recombination process for genetic programming. The
method is based on extracting the global information of
the promising solutions that appear during the genetic
search. The aim is to use this information to control
the crossover operation afterwards. A separate control
module is used to process the collected information.
This module guides the search process by sending
feedback to the genetic engine about the consequences
of possible recombination alternatives.
%0 Journal Article
%1 korkmaz:cgpa
%A Korkmaz, Emin Erkan
%A Ucoluk, Gokturk
%D 2004
%J IEEE Transactions on Systems, Man and Cybernetics,
Part B
%K Crossover, GP, algorithms, deceptive decision domain epistasis extraction, genetic global information problem, problems, process, programming, recombination search, searching, tree trees,
%N 4
%P 1730--1742
%R doi:10.1109/TSMCB.2004.828590
%T Controlled Genetic Programming Approach for the
Deceptive Domain
%U http://cse.yeditepe.edu.tr/~ekorkmaz/publication/IEEE2002.ps
%V 34
%X Traditional genetic programming (GP) randomly combines
subtrees by applying crossover. There is a growing
interest in methods that can control such recombination
operations in order to achieve faster convergence. In
this paper, a new approach is presented for guiding the
recombination process for genetic programming. The
method is based on extracting the global information of
the promising solutions that appear during the genetic
search. The aim is to use this information to control
the crossover operation afterwards. A separate control
module is used to process the collected information.
This module guides the search process by sending
feedback to the genetic engine about the consequences
of possible recombination alternatives.
@article{korkmaz:cgpa,
abstract = {Traditional genetic programming (GP) randomly combines
subtrees by applying crossover. There is a growing
interest in methods that can control such recombination
operations in order to achieve faster convergence. In
this paper, a new approach is presented for guiding the
recombination process for genetic programming. The
method is based on extracting the global information of
the promising solutions that appear during the genetic
search. The aim is to use this information to control
the crossover operation afterwards. A separate control
module is used to process the collected information.
This module guides the search process by sending
feedback to the genetic engine about the consequences
of possible recombination alternatives.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Korkmaz, Emin Erkan and Ucoluk, Gokturk},
biburl = {https://www.bibsonomy.org/bibtex/20d601c472cbc2775d6965df2724594be/brazovayeye},
doi = {doi:10.1109/TSMCB.2004.828590},
interhash = {32a98fa27535c318ee46a6aec1afa74f},
intrahash = {0d601c472cbc2775d6965df2724594be},
issn = {1083-4419},
journal = {IEEE Transactions on Systems, Man and Cybernetics,
Part B},
keywords = {Crossover, GP, algorithms, deceptive decision domain epistasis extraction, genetic global information problem, problems, process, programming, recombination search, searching, tree trees,},
month = {August},
notes = {INSPEC Accession Number:8111580 PMID: 15462440},
number = 4,
pages = {1730--1742},
timestamp = {2008-06-19T17:43:39.000+0200},
title = {Controlled Genetic Programming Approach for the
Deceptive Domain},
url = {http://cse.yeditepe.edu.tr/~ekorkmaz/publication/IEEE2002.ps},
volume = 34,
year = 2004
}