The performance of polyploid evolutionary algorithms is improved both by having many chromosomes and by having many copies of each chromosome on symbolic regression problems

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

@InProceedings{Cavill:Tpo:cec2005,

• author = "Rachel Cavill and Stephen L. Smith and Andy Tyrrell",
• title = "The performance of polyploid evolutionary algorithms is improved both by having many chromosomes and by having many copies of each chromosome on symbolic regression problems",
• booktitle = "Proceedings of the 2005 IEEE Congress on Evolutionary Computation",
• year = "2005",
• editor = "David Corne and Zbigniew Michalewicz and Bob McKay and Gusz Eiben and David Fogel and Carlos Fonseca and Garrison Greenwood and Gunther Raidl and Kay Chen Tan and Ali Zalzala",
• pages = "935--941",
• address = "Edinburgh, Scotland, UK",
• month = "2-5 " # sep,
• publisher = "IEEE Press",
• volume = "1",
• keywords = "genetic algorithms, genetic programming, biology, cellular biophysics, evolutionary computation, regression analysis, multiple chromosomes, polyploid evolutionary algorithm, symbolic regression problem",
• ISBN = "0-7803-9363-5",
• URL = "http://ieeexplore.ieee.org/servlet/opac?punumber=10417&isvol=1",
• URL = "http://ieeexplore.ieee.org/servlet/opac?punumber=10417",
• DOI = "doi:10.1109/CEC.2005.1554783",
• abstract = "This paper presents important new findings for a new method for evolving individual programs with multiple chromosomes. Previous results have shown that evolving individuals with multiple chromosomes produced improved results over evolving individuals with a single chromosome. The multiple chromosomes are organised along two axes; there are a number of different chromosomes and a number of copies of each chromosome. This paper investigates the effects which these two axes have on the performance of the algorithm; whether the improvement in performance comes from just one of these features or whether it is a combination of them both",
• notes = "Last author is NOT Terrell",

}

Genetic Programming entries for Rachel Cavill Stephen L Smith Andrew M Tyrrell

Citations