Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{1144155,
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author = "Darrell Whitley and Marc Richards and
Ross Beveridge and Andre' {da Motta Salles Barreto}",
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title = "Alternative evolutionary algorithms for evolving
programs: evolution strategies and steady state {GP}",
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booktitle = "{GECCO 2006:} Proceedings of the 8th annual conference
on Genetic and evolutionary computation",
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year = "2006",
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editor = "Maarten Keijzer and Mike Cattolico and Dirk Arnold and
Vladan Babovic and Christian Blum and Peter Bosman and
Martin V. Butz and Carlos {Coello Coello} and
Dipankar Dasgupta and Sevan G. Ficici and James Foster and
Arturo Hernandez-Aguirre and Greg Hornby and
Hod Lipson and Phil McMinn and Jason Moore and Guenther Raidl and
Franz Rothlauf and Conor Ryan and Dirk Thierens",
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volume = "1",
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ISBN = "1-59593-186-4",
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pages = "919--926",
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address = "Seattle, Washington, USA",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco2006/docs/p919.pdf",
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DOI = "doi:10.1145/1143997.1144155",
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publisher = "ACM Press",
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publisher_address = "New York, NY, 10286-1405, USA",
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month = "8-12 " # jul,
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organisation = "ACM SIGEVO (formerly ISGEC)",
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keywords = "genetic algorithms, genetic programming, evolution
strategies, ES, steady-state genetic algorithms,
Automatic Programming, Program Synthesis",
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size = "8 pages",
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abstract = "In contrast with the diverse array of genetic
algorithms, the Genetic Programming (GP) paradigm is
usually applied in a relatively uniform manner.
Heuristics have developed over time as to which
replacement strategies and selection methods are best.
The question addressed in this paper is relatively
simple: since there are so many variants of
evolutionary algorithm, how well do some of the other
well known forms of evolutionary algorithm perform when
used to evolve programs trees using s-expressions as
the representation? Our results suggest a wide range of
evolutionary algorithms are all equally good at
evolving programs, including the simplest evolution
strategies",
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notes = "GECCO-2006 A joint meeting of the fifteenth
international conference on genetic algorithms
(ICGA-2006) and the eleventh annual genetic programming
conference (GP-2006).
ACM Order Number 910060
Winner best paper.",
- }
Genetic Programming entries for
L Darrell Whitley
Marc D Richards
J Ross Beveridge
Andre da Motta Salles Barreto
Citations