Neutrality and the Evolvability of Boolean Function Landscape
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{yu:2001:EuroGP_neutrality,
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author = "Tina Yu and Julian Miller",
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title = "Neutrality and the Evolvability of {Boolean} Function
Landscape",
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booktitle = "Genetic Programming, Proceedings of EuroGP'2001",
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year = "2001",
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editor = "Julian F. Miller and Marco Tomassini and
Pier Luca Lanzi and Conor Ryan and Andrea G. B. Tettamanzi and
William B. Langdon",
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volume = "2038",
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series = "LNCS",
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pages = "204--217",
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address = "Lake Como, Italy",
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publisher_address = "Berlin",
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month = "18-20 " # apr,
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organisation = "EvoNET",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming, Neutrality,
Evolvability, Boolean function landscape, Neutral
mutation, Exploration vs. Exploitation, Graph-based
Genetic Programming",
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ISBN = "3-540-41899-7",
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URL = "http://www.cs.mun.ca/~tinayu/index_files/addr/public_html/neutrality.pdf",
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DOI = "doi:10.1007/3-540-45355-5_16",
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size = "14 pages",
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abstract = "This work is a study of neutrality in the context of
Evolutionary Computation systems. In particular, we
introduce the use of explicit neutrality with an
integer string coding scheme to allow neutrality to be
measured during evolution. We tested this method on a
Boolean benchmark problem. The experimental results
indicate that there is a positive relationship between
neutrality and evolvability: neutrality improves
evolvability. We also identify four characteristics of
adaptive/neutral mutations that are associated with
high evolvability. They may be the ingredients in
designing effective Evolutionary Computation systems
for the Boolean class problem.",
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notes = "EuroGP'2001, part of \cite{miller:2001:gp}",
- }
Genetic Programming entries for
Tina Yu
Julian F Miller
Citations