Finding Needles in Haystacks is not Hard with Neutrality

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{yu:2002:EuroGP,

• title = "Finding Needles in Haystacks is not Hard with Neutrality",
• author = "Tina Yu and Julian F. Miller",
• editor = "James A. Foster and Evelyne Lutton and Julian Miller and Conor Ryan and Andrea G. B. Tettamanzi",
• booktitle = "Genetic Programming, Proceedings of the 5th European Conference, EuroGP 2002",
• volume = "2278",
• series = "LNCS",
• pages = "13--25",
• publisher = "Springer-Verlag",
• address = "Kinsale, Ireland",
• publisher_address = "Berlin",
• month = "3-5 " # apr,
• year = "2002",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-43378-3",
• URL = "http://www.cs.mun.ca/~tinayu/index_files/addr/public_html/EuroGP2002.pdf",
• DOI = "doi:10.1007/3-540-45984-7_2",
• abstract = "We propose building neutral networks in needle-in-haystack fitness landscapes to assist an evolutionary algorithm to perform search. The experimental results on four different problems show that this approach improves the search success rates in most cases. In situations where neutral networks do not give performance improvement, no impairment occurs either. We also tested a hypothesis proposed in our previous work. The results support the hypothesis: when the ratio of adaptive/neutral mutations during neutral walk is close to that of fitness improvement step, the evolutionary search has a high success rate. Moreover, the ratio magnitudes indicate that more neutral mutations (than adaptive mutations) are required for the algorithms to find a solution in this type of search space.",
• notes = "EuroGP'2002, part of \cite{lutton:2002:GP} See also \cite{Yu:2006:AL}",

}

Genetic Programming entries for Tina Yu Julian F Miller

Citations