Cooperative Coevolution of Automatically Defined Functions with Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Alejandro Sosa-Ascencio and 
                 Manuel Valenzuela-Rendon and Hugo Terashima-Marin",
  booktitle =    "11th Mexican International Conference on Artificial
                 Intelligence (MICAI 2012)",
  title =        "Cooperative Coevolution of Automatically Defined
                 Functions with Gene Expression Programming",
  year =         "2012",
  pages =        "89--94",
  address =      "San Luis Potosi",
  month =        oct # " 27-" # nov # " 4",
  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",
  isbn13 =       "978-1-4673-4731-0",
  DOI =          "doi:10.1109/MICAI.2012.15",
  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