Learning of symbiotic relations among agents by using neural networks

Kotaro Hirasawa; Hidemasa Yoshida; Katsushige Nakanishi; Jinglu Hu; Junichi Murata

Learning of symbiotic relations among agents by using neural networks

Kotaro Hirasawa^*, Hidemasa Yoshida, Katsushige Nakanishi, Jinglu Hu, Junichi Murata

^*この研究の対応する著者

研究成果: Paper › 査読

抄録

Symbiotic relation among agents is regarded as one of the most basic relations in the complex systems. In this paper, a method for constructing the required symbiotic relations among the agents is proposed, where the agent is made up of a layered neural network and its parameters are trained in order to realize the required symbiotic relations. From simulations of the ecosystems, whose agent corresponds to the species, it has been clarified that the proposed method can give an ecosystem model with more flexible and more powerful representation abilities than the conventional Lotka-Volterra model.

本文言語	English
ページ	583-588
ページ数	6
出版ステータス	Published - 2002 1月 1
外部発表	はい
イベント	2002 International Joint Conference on Neural Networks (IJCNN '02) - Honolulu, HI, United States 継続期間: 2002 5月 12 → 2002 5月 17

Conference

Conference	2002 International Joint Conference on Neural Networks (IJCNN '02)
国/地域	United States
City	Honolulu, HI
Period	02/5/12 → 02/5/17

ASJC Scopus subject areas

ソフトウェア
人工知能

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引用スタイル

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AU - Yoshida, Hidemasa

AU - Nakanishi, Katsushige

AU - Hu, Jinglu

AU - Murata, Junichi

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Y1 - 2002/1/1

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Learning of symbiotic relations among agents by using neural networks

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Conference

ASJC Scopus subject areas

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