Online learning of genetic network programming (GNP)

Shingo Mabu; Kotaro Hirasawa; Jinglu Hu; Junichi Murata

doi:10.1109/CEC.2002.1006254

Online learning of genetic network programming (GNP)

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, Junichi Murata

計測制御工学

研究成果: Contribution to conference › Paper › 査読

20 被引用数 (Scopus)

抄録

A new evolutionary computation method called genetic network programming (GNP) was proposed recently. In this paper, an online learning method for GNP is proposed. This method uses Q learning to improve its state transition rules so that it can make GNP adapt to dynamic environments efficiently.

本文言語	英語
ページ	321-326
ページ数	6
DOI	https://doi.org/10.1109/CEC.2002.1006254
出版ステータス	出版済み - 2002
イベント	2002 Congress on Evolutionary Computation, CEC 2002 - Honolulu, HI, 米国継続期間: 5 12 2002 → 5 17 2002

その他

その他	2002 Congress on Evolutionary Computation, CEC 2002
国/地域	米国
City	Honolulu, HI
Period	5/12/02 → 5/17/02

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10.1109/CEC.2002.1006254

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title = "Online learning of genetic network programming (GNP)",

abstract = "A new evolutionary computation method called genetic network programming (GNP) was proposed recently. In this paper, an online learning method for GNP is proposed. This method uses Q learning to improve its state transition rules so that it can make GNP adapt to dynamic environments efficiently.",

author = "Shingo Mabu and Kotaro Hirasawa and Jinglu Hu and Junichi Murata",

year = "2002",

doi = "10.1109/CEC.2002.1006254",

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AU - Mabu, Shingo

AU - Hirasawa, Kotaro

AU - Hu, Jinglu

AU - Murata, Junichi

PY - 2002

Y1 - 2002

N2 - A new evolutionary computation method called genetic network programming (GNP) was proposed recently. In this paper, an online learning method for GNP is proposed. This method uses Q learning to improve its state transition rules so that it can make GNP adapt to dynamic environments efficiently.

AB - A new evolutionary computation method called genetic network programming (GNP) was proposed recently. In this paper, an online learning method for GNP is proposed. This method uses Q learning to improve its state transition rules so that it can make GNP adapt to dynamic environments efficiently.

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U2 - 10.1109/CEC.2002.1006254

DO - 10.1109/CEC.2002.1006254

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EP - 326

T2 - 2002 Congress on Evolutionary Computation, CEC 2002

Y2 - 11 May 2002 through 16 May 2002

ER -

Online learning of genetic network programming (GNP)

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その他

All Science Journal Classification (ASJC) codes

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