Multi Agent Systems with Symbiotic Learning and Evolution using GNP

Eguchi Toru, Takayuki Furuzuki, Murata Junichi, Hirasawa Kotaro

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Recently, various attempts relevant to Multi Agent Systems (MAS) which is one of the most promising systems based on Distributed Artificial Intelligence have been studied to control large and complicated systems efficiently. In these trends of MAS, Multi Agent Systems with Symbiotic Learning and Evolution named Masbiole has been proposed. In Masbiole, symbiotic phenomena among creatures are considered in the process of learning and evolution of MAS. So we can expect more flexible and sophisticated solutions than conventional MAS. In this paper, we apply Masbiole to Iterative Prisoner's Dilemma Games (IPD Games) using Genetic Network Programming (GNP) which is a newly developed evolutionary computation method for constituting agents. Some characteristics of Masbiole using GNP in IPD Games are clarified.

Original languageEnglish
Pages (from-to)517-526
Number of pages10
JournalIEEJ Transactions on Electronics, Information and Systems
Volume123
Issue number3
DOIs
Publication statusPublished - 2003
Externally publishedYes

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Keywords

  • evolutionary computation
  • multi agent system
  • prisoner's dilemma games
  • symbiotic phenomena

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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