Cooperative Coevolution of Automatically Defined Functions with Gene Expression Programming
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- @InProceedings{Sosa-Ascencio:2012:MICAI,
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author = "Alejandro Sosa-Ascencio and
Manuel Valenzuela-Rendon and Hugo Terashima-Marin",
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booktitle = "11th Mexican International Conference on Artificial
Intelligence (MICAI 2012)",
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title = "Cooperative Coevolution of Automatically Defined
Functions with Gene Expression Programming",
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year = "2012",
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pages = "89--94",
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address = "San Luis Potosi",
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month = oct # " 27-" # nov # " 4",
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keywords = "genetic algorithms, genetic programming, Gene
Expression Programming, regression analysis, ADF, GEP,
automatically defined function, cooperative
coevolution, evolutionary approach, gene expression
programming, symbolic regression problem, vgGA
framework, virtual gene genetic algorithm, Biological
cells, Indexes, Mathematical model, Sociology,
Statistics, automatically defined functions,
cooperative coevolution, symbolic regression problems",
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isbn13 = "978-1-4673-4731-0",
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DOI = "doi:10.1109/MICAI.2012.15",
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abstract = "The decomposition of problems into smaller elements is
a widespread approach. In this paper we consider two
approaches that are based over the principle to
segmentation to problems for the resolution of
resultant sub-components. On one hand, we have
Automatically Defined Functions (ADFs), which
originally emerged as a refinement of genetic
programming for reuse code and modularise programs into
smaller components, and on the other hand, we
incorporated co evolution to the implementation of
ADFs, we present a cooperative co evolutionary-based
approach to the problem of developing ADFs, we
implemented a module of Gene Expression Programming
(GEP) for the virtual gene Genetic Algorithm (vgGA)
framework, and tested the co evolution of ADFs in three
symbolic regression problems, comparing it with a
conventional genetic algorithm. Our results show that
on a simple function a conventional genetic algorithm
performs better than our co evolutionary approach, but
on a more complex functions the conventional genetic
algorithm is outperformed by our co evolutionary
approach. Also, we present an algorithm to implement
GEP in a minimally invasive way in almost any genetic
algorithm implementation.",
-
notes = "Also known as \cite{6387221}",
- }
Genetic Programming entries for
Alejandro Sosa-Ascencio
Manuel Valenzuela-Rendon
Hugo Terashima-Marin
Citations