Evolving search spaces to emphasize the performance difference of real-coded crossovers using genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Shirakawa:2010:cec,
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author = "Shinichi Shirakawa and Noriko Yata and
Tomoharu Nagao",
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title = "Evolving search spaces to emphasize the performance
difference of real-coded crossovers using genetic
programming",
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booktitle = "IEEE Congress on Evolutionary Computation (CEC 2010)",
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year = "2010",
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address = "Barcelona, Spain",
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month = "18-23 " # jul,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming, cartesian
genetic programming",
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isbn13 = "978-1-4244-6910-9",
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abstract = "When we evaluate the search performance of an
evolutionary computation (EC) technique, we usually
apply it to typical benchmark functions and evaluate
its performance in comparison to other techniques. In
experiments on limited benchmark functions, it can be
difficult to understand the features of each technique.
In this paper, the search spaces that emphasise the
performance difference of EC techniques are evolved by
Cartesian genetic programming. We focus on a real-coded
genetic algorithm, which is a type of genetic algorithm
that has a real-valued vector as a chromosome. In
particular, we generate search spaces using the
performance difference of real-coded crossovers. In the
experiments, we evolve the search spaces using the
combination of three types of real-coded crossovers. As
a result of our experiments, the search spaces that
exhibit the largest performance difference of two
crossovers are generated for all the combinations.",
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DOI = "doi:10.1109/CEC.2010.5586065",
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notes = "WCCI 2010. Also known as \cite{5586065}",
- }
Genetic Programming entries for
Shinichi Shirakawa
Noriko Yata
Tomoharu Nagao
Citations