A Data Structure for Improved GP Analysis via Efficient Computation and Visualisation of Population Measures
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{ekart:2004:eurogp,
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author = "Aniko Ekart and Steven Gustafson",
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title = "A Data Structure for Improved GP Analysis via
Efficient Computation and Visualisation of Population
Measures",
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booktitle = "Genetic Programming 7th European Conference, EuroGP
2004, Proceedings",
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year = "2004",
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editor = "Maarten Keijzer and Una-May O'Reilly and
Simon M. Lucas and Ernesto Costa and Terence Soule",
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volume = "3003",
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series = "LNCS",
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pages = "35--46",
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address = "Coimbra, Portugal",
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publisher_address = "Berlin",
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month = "5-7 " # apr,
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organisation = "EvoNet",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-21346-5",
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URL = "http://www.sztaki.hu/~ekart/eurgp4.ps",
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URL = "http://www.cs.nott.ac.uk/~smg/research/publications/eurogp-itree-2004.pdf",
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DOI = "doi:10.1007/978-3-540-24650-3_4",
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abstract = "Population measures for genetic programs are defined
and analysed in an attempt to better understand the
behaviour of genetic programming. Some measures are
simple, but do not provide sufficient insight. The more
meaningful ones are complex and take extra computation
time. Here we present a unified view on the computation
of population measures through an information
hyper-tree (iTree). The iTree allows for a unified and
efficient calculation of population measures via a
basic tree traversal.",
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notes = "Part of \cite{keijzer:2004:GP} EuroGP'2004 held in
conjunction with EvoCOP2004 and EvoWorkshops2004",
- }
Genetic Programming entries for
Aniko Ekart
Steven M Gustafson
Citations