Advanced Population Diversity Measures in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{burke:ppsn2002:pp341,
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author = "Edmund Burke and Steven Gustafson and
Graham Kendall and Natalio Krasnogor",
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title = "Advanced Population Diversity Measures in Genetic
Programming",
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booktitle = "Parallel Problem Solving from Nature - PPSN VII",
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address = "Granada, Spain",
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month = "7-11 " # sep,
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pages = "341--350",
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year = "2002",
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editor = "Juan J. Merelo-Guervos and Panagiotis Adamidis and
Hans-Georg Beyer and Jose-Luis Fernandez-Villacanas and
Hans-Paul Schwefel",
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number = "2439",
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series = "Lecture Notes in Computer Science, LNCS",
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publisher = "Springer-Verlag",
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URL = "http://www.gustafsonresearch.com/research/publications/ppsn-2002.pdf",
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URL = "http://www.cs.nott.ac.uk/~smg/research/publications/ppsn-2002.ps",
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URL = "http://www.cs.nott.ac.uk/~smg/research/publications/ppsn-2002.pdf",
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URL = "http://slater.chem.nott.ac.uk/~natk/Public/PAPERS/gp-ppsn2002.ps.Z",
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URL = "http://citeseer.ist.psu.edu/529057.html",
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DOI = "doi:10.1007/3-540-45712-7_33",
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keywords = "genetic algorithms, genetic programming, Theory of EC,
Evolution dynamics",
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ISBN = "3-540-44139-5",
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abstract = "This paper presents a survey and comparison of
significant diversity measures in the genetic
programming literature. This study builds on previous
work by the authors to gain a deeper understanding of
the conditions under which genetic programming
evolution is successful. Three benchmark problems
(Artificial Ant, Symbolic Regression and Even-5-Parity)
are used to illustrate different diversity measures and
to analyse their correlation with performance. Results
show that measures of population diversity based on
edit distances and phenotypic diversity suggest that
successful evolution occurs when populations converge
to a similar structure but with high fitness
diversity.",
- }
Genetic Programming entries for
Edmund Burke
Steven M Gustafson
Graham Kendall
Natalio Krasnogor
Citations