Multi Agent Systems with Symbiotic Learning and Evolution -Masbiole- and Its Application

Kotaro Hirasawa, Katsushige Nakanishi, Toru Eguchi, Takayuki Furuzuki

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Recently, systems are becoming more complex and larger than ever, so numerous attempts have been made to introduce biological features into artificial systems, because many biological systems in the nature exist as one of the most complex systems. Multi agent system with symbiotic learning and evolution have been recently proposed. It is named Masbiole. In this paper, Masbiole is reviewed and the method for evolving multi agent systems is proposed. From simulations on a multi objective knapsack problem, it has been clarified that Masbiole has better performance than that of conventional multi objective genetic algorithms.

Original languageEnglish
Pages (from-to)67-74
Number of pages8
JournalIEEJ Transactions on Electronics, Information and Systems
Volume123
Issue number1
DOIs
Publication statusPublished - 2003
Externally publishedYes

Fingerprint

Multi agent systems
Biological systems
Large scale systems
Genetic algorithms

Keywords

  • evolution
  • learning
  • multi agent system
  • pareto optimal solutions
  • symbiosis

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Multi Agent Systems with Symbiotic Learning and Evolution -Masbiole- and Its Application. / Hirasawa, Kotaro; Nakanishi, Katsushige; Eguchi, Toru; Furuzuki, Takayuki.

In: IEEJ Transactions on Electronics, Information and Systems, Vol. 123, No. 1, 2003, p. 67-74.

Research output: Contribution to journalArticle

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