Genetic network programming with simplified genetic operators

Xianneng Li, Wen He, Kotaro Hirasawa

研究成果: Conference contribution

13 被引用数 (Scopus)

抄録

Recently, a novel type of evolutionary algorithms (EAs), called Genetic Network Programming (GNP), has been proposed. Inspired by the complex human brain structures, GNP develops a distinguished directed graph structure for its individual representations, consequently showing an excellent expressive ability for modelling a range of complex problems. This paper is dedicated to reveal GNP's unique features. Accordingly, simplified genetic operators are proposed to highlight such features of GNP, reduce its computational effort and provide better results. Experimental results are presented to confirm its effectiveness over original GNP and several state-of-the-art algorithms.

本文言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ページ51-58
ページ数8
8227 LNCS
PART 2
DOI
出版ステータスPublished - 2013
イベント20th International Conference on Neural Information Processing, ICONIP 2013 - Daegu, Korea, Republic of
継続期間: 2013 11月 32013 11月 7

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
番号PART 2
8227 LNCS
ISSN(印刷版)03029743
ISSN(電子版)16113349

Other

Other20th International Conference on Neural Information Processing, ICONIP 2013
国/地域Korea, Republic of
CityDaegu
Period13/11/313/11/7

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)
  • 理論的コンピュータサイエンス

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