Multi Agent Systems with Symbiotic Learning and Evolution using GNP

Eguchi Toru; Hu Jinglu; Murata Junichi; Hirasawa Kotaro

doi:10.1541/ieejeiss.123.517

Multi Agent Systems with Symbiotic Learning and Evolution using GNP

Eguchi Toru, Hu Jinglu, Murata Junichi, Hirasawa Kotaro

Research output: Contribution to journal › Article › peer-review

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 language	English
Pages (from-to)	517-526
Number of pages	10
Journal	IEEJ Transactions on Electronics, Information and Systems
Volume	123
Issue number	3
DOIs	https://doi.org/10.1541/ieejeiss.123.517
Publication status	Published - 2003 Jan
Externally published	Yes

Keywords

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

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1541/ieejeiss.123.517

Cite this

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title = "Multi Agent Systems with Symbiotic Learning and Evolution using GNP",

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.",

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AU - Toru, Eguchi

AU - Jinglu, Hu

AU - Junichi, Murata

AU - Kotaro, Hirasawa

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AB - 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.

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Multi Agent Systems with Symbiotic Learning and Evolution using GNP

Abstract

Keywords

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