AdaGEP - An Adaptive Gene Expression Programming Algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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