Using Differential Evolution for GEP Constant Creation

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Qiongyun Zhang and Chi Zhou and Weimin Xiao and 
                 Peter C. Nelson and Xin Li",
  title =        "Using Differential Evolution for GEP Constant
  booktitle =    "Late breaking paper at Genetic and Evolutionary
                 Computation Conference {(GECCO'2006)}",
  year =         "2006",
  month =        "8-12 " # jul,
  editor =       "J{\"{o}}rn Grahl",
  address =      "Seattle, WA, USA",
  URL =          "",
  notes =        "Distributed on CD-ROM at GECCO-2006",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, DE",
  abstract =     "Gene Expression Programming (GEP) is a new
                 evolutionary algorithm that incorporates both the idea
                 of simple, linear chromosomes of fixed length used in
                 Genetic Algorithms (GAs) and the structure of different
                 sizes and shapes used in Genetic Programming (GP). As
                 with other genetic programming algorithms, GEP has
                 difficulty finding appropriate numeric constants for
                 terminal nodes in the expression trees. In this paper,
                 we describe a new approach of constant generation using
                 Differential Evolution (DE), which is a simple
                 real-valued GA that has proven to be robust and
                 efficient on parameter optimisation problems. 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 variants.",

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