Investigating the Baldwin Effect on Cartesian Genetic Programming Efficiency
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Khatir:2008:cec,
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author = "Mehrdad Khatir and Amir Hossein Jahangir and
Hamid Beigy",
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title = "Investigating the Baldwin Effect on Cartesian Genetic
Programming Efficiency",
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booktitle = "2008 IEEE World Congress on Computational
Intelligence",
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year = "2008",
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editor = "Jun Wang",
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pages = "2360--2364",
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address = "Hong Kong",
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month = "1-6 " # jun,
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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isbn13 = "978-1-4244-1823-7",
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file = "EC0549.pdf",
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DOI = "doi:10.1109/CEC.2008.4631113",
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abstract = "Cartesian Genetic Programming (CGP) has an unusual
genotype representation which makes it more efficient
than Genetic programming (GP) in digital circuit design
problem. However, to the best of our knowledge, all
methods used in evolutionary design of digital circuits
deal with rugged, complex search space, which results
in long running time to obtain successful evolution.
Therefore, employing a method to guide evolution in
these spaces can facilitate achieving more reasonable
results. It has been claimed that a two-step
evolutionary scenario caused by benefit and cost of
learning called Baldwin effect can guide evolution in
the biology and artificial life. Therefore, we have
been motivated to examine this effect on CGP. We
observe using this scenario the success rate and
evolution time of CGP improves dramatically especially
when size of chromosomes increases.",
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keywords = "genetic algorithms, genetic programming, Cartesian
Genetic Programming, Baldwin Effect, Phenotypic
Plasticity, Digital Circuit, Reinforcement Learning.",
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notes = "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
EPS and the IET.",
- }
Genetic Programming entries for
Mehrdad Khatir
Amir Hossein Jahangir
Hamid Beigy
Citations