Functional localization of genetic network programming and its application to a pursuit problem

Shinji Eto, Kotaro Hirasawa, Jinglu Hu

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

1 Citation (Scopus)

Abstract

According to the knowledge of brain science, it is suggested that there exists cerebral functional localization, which means that a specific part of the cerebrum is activated depending on various kinds of information human receives. The aim of this paper is to build an artificial model to realize functional localization based on Genetic Network Programming (GNP), a new evolutionary computation method recently developed. GNP has a directed graph structure suitable for realizing functional localization. We studied the basic characteristics of the proposed system by making GNP work in a functionally localized way.

Original languageEnglish
Title of host publicationProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Pages683-690
Number of pages8
Publication statusPublished - 2004 Sep 13
EventProceedings of the 2004 Congress on Evolutionary Computation, CEC2004 - Portland, OR, United States
Duration: 2004 Jun 192004 Jun 23

Publication series

NameProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Volume1

Conference

ConferenceProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
CountryUnited States
CityPortland, OR
Period04/6/1904/6/23

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Eto, S., Hirasawa, K., & Hu, J. (2004). Functional localization of genetic network programming and its application to a pursuit problem. In Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 (pp. 683-690). (Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004; Vol. 1).