Evolutionary Operator Self-Adaptation with Diverse Operators
Created by W.Langdon from
gp-bibliography.bib Revision:1.8120
- @InProceedings{kim:2012:EuroGP,
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author = "MinHyeok Kim and Robert Ian (Bob) McKay and
Dong-Kyun Kim and Xuan Hoai Nguyen",
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title = "Evolutionary Operator Self-Adaptation with Diverse
Operators",
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booktitle = "Proceedings of the 15th European Conference on Genetic
Programming, EuroGP 2012",
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year = "2012",
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month = "11-13 " # apr,
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editor = "Alberto Moraglio and Sara Silva and
Krzysztof Krawiec and Penousal Machado and Carlos Cotta",
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series = "LNCS",
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volume = "7244",
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publisher = "Springer Verlag",
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address = "Malaga, Spain",
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pages = "230--241",
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organisation = "EvoStar",
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isbn13 = "978-3-642-29138-8",
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DOI = "doi:10.1007/978-3-642-29139-5_20",
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keywords = "genetic algorithms, genetic programming, Adaptive
operator selection, Adaptive pursuit, Probability
matching, Multi-armed bandit, Evolutionary algorithm",
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abstract = "Operator adaptation in evolutionary computation has
previously been applied to either small numbers of
operators, or larger numbers of fairly similar ones.
This paper focuses on adaptation in algorithms offering
a diverse range of operators. We compare a number of
previously-developed adaptation strategies, together
with two that have been specifically designed for this
situation. Probability Matching and Adaptive Pursuit
methods performed reasonably well in this scenario, but
a strategy combining aspects of both performed better.
Multi-Arm Bandit techniques performed well when
parameter settings were suitably tailored to the
problem, but this tailoring was difficult, and
performance was very brittle when the parameter
settings were varied.",
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notes = "Part of \cite{Moraglio:2012:GP} EuroGP'2012 held in
conjunction with EvoCOP2012 EvoBIO2012, EvoMusArt2012
and EvoApplications2012",
- }
Genetic Programming entries for
MinHyeok Kim
R I (Bob) McKay
Dong-Kyun Kim
Nguyen Xuan Hoai
Citations