Functionally distributed systems using parallel Genetic Network Programming

Yiwen Zhang, Xianneng Li, Yang Yang, Shingo Mabu, Yi Jin, Kotaro Hirasawa

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

Abstract

Genetic Network Programming (GNP), one of the evolutionary computational methods, can generate behavior sequences of agents. In this paper, a new method named parallel GNP has been proposed and applied to functionally distributed systems consisted of several tasks. GNPs corresponding to several tasks in parallel GNP operate separately and independently but concurrently, dealing with the conflicts in task execution. Parallel GNP converges faster and has better fitness results than conventional GNP, which was shown by simulations comparing with conventional GNP on dynamic problems.

Original languageEnglish
Title of host publicationProceedings of the SICE Annual Conference
Pages2626-2630
Number of pages5
Publication statusPublished - 2010
EventSICE Annual Conference 2010, SICE 2010 - Taipei, Taiwan, Province of China
Duration: 2010 Aug 182010 Aug 21

Other

OtherSICE Annual Conference 2010, SICE 2010
CountryTaiwan, Province of China
CityTaipei
Period10/8/1810/8/21

Keywords

  • Evolutionary computation
  • Functionally distributed systems
  • Parallel genetic network programming

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Functionally distributed systems using parallel Genetic Network Programming'. Together they form a unique fingerprint.

  • Cite this

    Zhang, Y., Li, X., Yang, Y., Mabu, S., Jin, Y., & Hirasawa, K. (2010). Functionally distributed systems using parallel Genetic Network Programming. In Proceedings of the SICE Annual Conference (pp. 2626-2630). [5602493]