Using Differential Evolution for GEP Constant Creation

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Zhang:gecco06lbp,

• author = "Qiongyun Zhang and Chi Zhou and Weimin Xiao and Peter C. Nelson and Xin Li",
• title = "Using Differential Evolution for {GEP} Constant Creation",
• 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 = "http://gpbib.cs.ucl.ac.uk/gecco2006etc/papers/lbp130.pdf",
• 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

Citations