Improving gene expression programming performance by using differential evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Zhang:2007:ICMLA,
  title =        "Improving gene expression programming performance by
                 using differential evolution",
  author =       "Qiongyun Zhang and Chi Zhou and Weimin Xiao and 
                 Peter C. Nelson",
  booktitle =    "Sixth International Conference on Machine Learning and
                 Applications, ICMLA 2007",
  year =         "2007",
  month =        "13-15 " # dec,
  pages =        "31--37",
  address =      "Cincinnati, Ohio, USA",
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, evolutionary computation
                 differential evolution, evolutionary algorithm, linear
                 chromosome, symbolic regression, tree structure",
  DOI =          "doi:10.1109/ICMLA.2007.62",
  abstract =     "Gene Expression Programming (GEP) is an evolutionary
                 algorithm that incorporates both the idea of a simple,
                 linear chromosome of fixed length used in Genetic
                 Algorithms (GAs) and the tree structure of different
                 sizes and shapes used in Genetic Programming (GP). As
                 with other GP algorithms, GEP has difficulty finding
                 appropriate numeric constants for terminal nodes in the
                 expression trees. In this work, we describe a new
                 approach of constant generation using Differential
                 Evolution (DE), a real-valued GA robust and efficient
                 at parameter optimization. Our experimental results on
                 two symbolic regression problems show that the approach
                 significantly improves the performance of the GEP
                 algorithm. The proposed approach can be easily extended
                 to other Genetic Programming variations.",
  notes =        "also known as \cite{4457204}",
}

Genetic Programming entries for Qiongyun (Amy) Zhang Chi Zhou Weimin Xiao Peter C Nelson

Citations