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

K. Hirasawa*, M. Okubo, J. Hu, H. Katagiri, J. Murata

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

141 Citations (Scopus)


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
Number of pages7
Publication statusPublished - 2001 Jan 1
Externally publishedYes
EventCongress on Evolutionary Computation 2001 - Seoul, Korea, Republic of
Duration: 2001 May 272001 May 30


ConferenceCongress on Evolutionary Computation 2001
Country/TerritoryKorea, Republic of

ASJC Scopus subject areas

  • General Computer Science
  • General Engineering


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