AdaGEP - An Adaptive Gene Expression Programming Algorithm
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{conf/synasc/BautuBL07,
-
author = "Elena Bautu and Andrei Bautu and Henri Luchian",
-
title = "Ada{GEP} - An Adaptive Gene Expression Programming
Algorithm",
-
booktitle = "Proceedings of the Ninth International Symposium on
Symbolic and Numeric Algorithms for Scientific
Computing, {SYNASC} 2007",
-
year = "2007",
-
editor = "Viorel Negru and Tudor Jebelean and Dana Petcu and
Daniela Zaharie",
-
pages = "403--406",
-
address = "Timisoara, Romania",
-
month = sep # " 26-29",
-
publisher = "IEEE Computer Society",
-
keywords = "genetic algorithms, genetic programming, gene
expression programming",
-
isbn13 = "978-0-7695-3078-9",
-
DOI = "doi:10.1109/SYNASC.2007.51",
-
abstract = "Many papers focused on fine-tuning the gene expression
programming (GEP) operators or their application rates
in order to improve the performances of the algorithm.
Much less work was done on optimizing the structural
parameters of the chromosomes (i.e. number of genes and
gene size). This is probably due to the fact that the
no free lunch theorem states that no fixed values for
these parameters will ever suit all problems. To
counteract this fact, this paper presents a modified
GEP algorithm, called AdaGEP, which automatically
adapts the number of genes used by the chromosome. The
adaptation process takes place at chromosome level,
allowing chromosomes in the population to evolve with
different number of genes.",
-
notes = "p406 'The results presented in this paper demonstrate
the superiority of AdaGEP over GEP on symbolic
regression problems.'",
-
bibdate = "2008-11-28",
-
bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/synasc/synasc2007.html#BautuBL07",
- }
Genetic Programming entries for
Elena Bautu
Andrei Bautu
Henri Luchian
Citations