Symbiotic evolutional models in multiagent systems

Toru Eguchi; Kotaro Hirasawa; Jinglu Hu

doi:10.1109/CEC.2003.1299741

Symbiotic evolutional models in multiagent systems

Toru Eguchi, Kotaro Hirasawa, Jinglu Hu

Graduate School of Information, Production and Systems

Research output: Contribution to conference › Paper › peer-review

3 Citations (Scopus)

Abstract

Multiagent systems with symbiotic learning and evolution (Masbiole) has been proposed as a new learning and evolutionary method for multiagent systems (MAS) recently, which is based on symbiotic phenomena among creatures. A symbiotic evolutional model of Masbiole is proposed using genetic network programming (GNP), which has been also proposed as one of the evolutionary computations. In the simulations, the proposal Masbiole is applied to the tile-world model and various characteristics of Masbiole have been clarified.

Original language	English
Pages	739-746
Number of pages	8
DOIs	https://doi.org/10.1109/CEC.2003.1299741
Publication status	Published - 2003 Jan 1
Event	2003 Congress on Evolutionary Computation, CEC 2003 - Canberra, ACT, Australia Duration: 2003 Dec 8 → 2003 Dec 12

Conference

Conference	2003 Congress on Evolutionary Computation, CEC 2003
Country/Territory	Australia
City	Canberra, ACT
Period	03/12/8 → 03/12/12

ASJC Scopus subject areas

Computational Mathematics

Access to Document

10.1109/CEC.2003.1299741

Cite this

@conference{6b49a47b60d64765b181ea30e1e684be,

title = "Symbiotic evolutional models in multiagent systems",

abstract = "Multiagent systems with symbiotic learning and evolution (Masbiole) has been proposed as a new learning and evolutionary method for multiagent systems (MAS) recently, which is based on symbiotic phenomena among creatures. A symbiotic evolutional model of Masbiole is proposed using genetic network programming (GNP), which has been also proposed as one of the evolutionary computations. In the simulations, the proposal Masbiole is applied to the tile-world model and various characteristics of Masbiole have been clarified.",

author = "Toru Eguchi and Kotaro Hirasawa and Jinglu Hu",

year = "2003",

month = jan,

day = "1",

doi = "10.1109/CEC.2003.1299741",

language = "English",

pages = "739--746",

note = "2003 Congress on Evolutionary Computation, CEC 2003 ; Conference date: 08-12-2003 Through 12-12-2003",

}

TY - CONF

T1 - Symbiotic evolutional models in multiagent systems

AU - Eguchi, Toru

AU - Hirasawa, Kotaro

AU - Hu, Jinglu

PY - 2003/1/1

Y1 - 2003/1/1

N2 - Multiagent systems with symbiotic learning and evolution (Masbiole) has been proposed as a new learning and evolutionary method for multiagent systems (MAS) recently, which is based on symbiotic phenomena among creatures. A symbiotic evolutional model of Masbiole is proposed using genetic network programming (GNP), which has been also proposed as one of the evolutionary computations. In the simulations, the proposal Masbiole is applied to the tile-world model and various characteristics of Masbiole have been clarified.

AB - Multiagent systems with symbiotic learning and evolution (Masbiole) has been proposed as a new learning and evolutionary method for multiagent systems (MAS) recently, which is based on symbiotic phenomena among creatures. A symbiotic evolutional model of Masbiole is proposed using genetic network programming (GNP), which has been also proposed as one of the evolutionary computations. In the simulations, the proposal Masbiole is applied to the tile-world model and various characteristics of Masbiole have been clarified.

UR - http://www.scopus.com/inward/record.url?scp=31744442702&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=31744442702&partnerID=8YFLogxK

U2 - 10.1109/CEC.2003.1299741

DO - 10.1109/CEC.2003.1299741

M3 - Paper

AN - SCOPUS:31744442702

SP - 739

EP - 746

T2 - 2003 Congress on Evolutionary Computation, CEC 2003

Y2 - 8 December 2003 through 12 December 2003

ER -

Symbiotic evolutional models in multiagent systems

Abstract

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this