Binary Representation in Gene Expression Programming: Towards a Better Scalability

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{conf/isda/Moreno-TorresLG09,

• title = "Binary Representation in Gene Expression Programming: Towards a Better Scalability",
• author = "Jose Garcia Moreno-Torres and Xavier Llora and David E. Goldberg",
• booktitle = "Ninth International Conference on Intelligent Systems Design and Applications, ISDA '09",
• year = "2009",
• month = "30 " # nov # "-2 " # dec,
• pages = "1441--1444",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/isda/isda2009.html#Moreno-TorresLG09",
• keywords = "genetic algorithms, genetic programming, gene expression programming, machine learning, classifier systems",
• DOI = "doi:10.1109/ISDA.2009.33",
• publisher = "IEEE Computer Society",
• abstract = "One of the main problems that arises when using gene expression programming (GEP) conditions in learning classifier systems is the increasing number of symbols present as the problem size grows. When doing model-building LCS, this issue limits the scalability of such a technique, due to the cost required. This paper proposes a binary representation of GEP chromosomes to palliate the computation requirements needed. A theoretical reasoning behind the proposed representation is provided, along with empirical validation.",
• notes = "Also known as \cite{5363972}",

}

Genetic Programming entries for Jose Garcia Moreno-Torres Xavier Llora David E Goldberg

Citations