Investigation of Constant Creation Techniques in the Context of Gene Expression Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{li:2004:lbp,
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author = "Xin Li and Chi Zhou and Peter C. Nelson and
Thomas M. Tirpak",
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title = "Investigation of Constant Creation Techniques in the
Context of Gene Expression Programming",
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booktitle = "Late Breaking Papers at the 2004 Genetic and
Evolutionary Computation Conference",
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year = "2004",
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editor = "Maarten Keijzer",
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address = "Seattle, Washington, USA",
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month = "26 " # jul,
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keywords = "genetic algorithms, genetic programming, GEP",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco2004/LBP023.pdf",
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URL = "http://www.cs.uic.edu/~xli1/papers/GEPConstantCreation(GECCO04_LBP).pdf",
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abstract = "Gene Expression Programming (GEP) is a new technique
of Genetic Programming (GP) that implements a linear
genotype representation. It uses fixed-length
chromosomes to represent expression trees of different
shapes and sizes, which results in unconstrained search
of the genome space while still ensuring validity of
the programs output. However, GEP has some difficulty
in discovering suitable function structures because the
genetic operators are more disruptive than traditional
tree-based GP. One possible remedy is to specifically
assist the algorithm in discovering useful numeric
constants. In this paper, the effectiveness of several
constant creation techniques for GEP has been
investigated through two symbolic regression benchmark
problems. Our experimental results show that constant
creation methods applied to the whole population for
selected generations perform better than methods that
are applied only to the best individuals. The proposed
tune-up process for the entire population can
significantly improve the average fitness of the best
solutions.",
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notes = "Part of \cite{keijzer:2004:GECCO:lbp}",
- }
Genetic Programming entries for
Xin Li
Chi Zhou
Peter C Nelson
Thomas M Tirpak
Citations