文献
J-GLOBAL ID:202002246981071441
整理番号:20A2618948
ネットワーク内輻輳制御への分散強化学習アプローチ【JST・京大機械翻訳】
A Distributed Reinforcement Learning Approach to In-network Congestion Control
著者 (5件):
Mai Tianle
(State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications,Beijing,China)
,
Yao Haipeng
(State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications,Beijing,China)
,
Zhang Xing
(Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Posts and Telecommunications,Beijing,China)
,
Xiong Zehui
(School of Computer Science and Engineering, Nanyang Technological University,Singapore)
,
Niyato Dusit
(School of Computer Science and Engineering, Nanyang Technological University,Singapore)
資料名:
IEEE Conference Proceedings
(IEEE Conference Proceedings)
巻:
2020
号:
ICCC
ページ:
817-822
発行年:
2020年
JST資料番号:
W2441A
資料種別:
会議録 (C)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)