Comparison between Genetic Network Programming(gnp) and Genetic Programming(gp)

K. Hirasawa, M. Okubo, Takayuki Furuzuki, H. Katagiri, J. Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

126 Citations (Scopus)

Abstract

Recently, many methods of evolutionary computation such as Genetic Algorithm(GA) and Genetic Programming(GP) have been developed as a basic tool for modeling and optimizing the complex systems. Generally speaking, GA has the genome of string structure, while the genome in GP is the tree structure. Therefore, GP is suitable to construct the complicated programs, which can be applied to many real world problems. But, GP might be sometimes difficult to search for a solution because of its bloat. In this paper, a new evolutionary method named Genetic Network Programming(GNP), whose genome is network structure is proposed to overcome the low searching efficiency of GP and is applied to the problem on the evolution of behaviors of ants in order to study the effectiveness of GNP. In addition, the comparison of the performances between GNP and GP is carried out in simulations on ants behaviors.

Original languageEnglish
Title of host publicationProceedings of the IEEE Conference on Evolutionary Computation, ICEC
Pages1276-1282
Number of pages7
Volume2
Publication statusPublished - 2001
Externally publishedYes
EventCongress on Evolutionary Computation 2001 - Seoul
Duration: 2001 May 272001 May 30

Other

OtherCongress on Evolutionary Computation 2001
CitySeoul
Period01/5/2701/5/30

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ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

Cite this

Hirasawa, K., Okubo, M., Furuzuki, T., Katagiri, H., & Murata, J. (2001). Comparison between Genetic Network Programming(gnp) and Genetic Programming(gp). In Proceedings of the IEEE Conference on Evolutionary Computation, ICEC (Vol. 2, pp. 1276-1282)