文献
J-GLOBAL ID:202202267995383624
整理番号:22A0958854
マルチUAV IoTネットワークにおける関節軌道設計のための深層強化学習アプローチ【JST・京大機械翻訳】
Deep Reinforcement Learning Approach for Joint Trajectory Design in Multi-UAV IoT Networks
著者 (5件):
Xu Shu
(School of Infomation Science and Engineering, National Mobile Communications Research Laboratory, Southeast University, Nanjing, China)
,
Zhang Xiangyu
(School of Infomation Science and Engineering, National Mobile Communications Research Laboratory, Southeast University, Nanjing, China)
,
Li Chunguo
(School of Infomation Science and Engineering, National Mobile Communications Research Laboratory, Southeast University, Nanjing, China)
,
Wang Dongming
(School of Infomation Science and Engineering, National Mobile Communications Research Laboratory, Southeast University, Nanjing, China)
,
Yang Luxi
(School of Infomation Science and Engineering, National Mobile Communications Research Laboratory, Southeast University, Nanjing, China)
資料名:
IEEE Transactions on Vehicular Technology
(IEEE Transactions on Vehicular Technology)
巻:
71
号:
3
ページ:
3389-3394
発行年:
2022年
JST資料番号:
C0244A
ISSN:
0018-9545
CODEN:
ITVTAB
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)