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6 results found in all.
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1Deep reinforcement learning: a survey
Author(s):Hao-nan Wang, Ning Liu, Yi-yun Zhang, Da-wei Feng, Feng Huang, Dong-sheng Li, Yi-ming Zhang  Clicked:4929  Download:3063  Cited:0  <Full Text>  <PPT> 1380
Frontiers of Information Technology & Electronic Engineering  2020 Vol.21 No.12 P.1726-1744  DOI:10.1631/FITEE.1900533
2Multi-agent deep reinforcement learning for end–edge orchestrated resource allocation in industrial wireless networks
Author(s):Xiaoyu LIU, Chi XU, Haibin YU, Peng ZENG  Clicked:3971  Download:4349  Cited:0  <Full Text>  <PPT> 728
Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.1 P.47-60  DOI:10.1631/FITEE.2100331
3Towards autonomous and optimal excavation of shield machine: a deep reinforcement learning-based approach
Author(s):Ya-kun ZHANG, Guo-fang GONG, Hua-yong YANG, Yu-xi CHEN, Geng-lin CHEN  Clicked:1816  Download:1393  Cited:0  <Full Text>  <PPT> 294
Journal of Zhejiang University Science A  2022 Vol.23 No.6 P.458-478  DOI:10.1631/jzus.A2100325
4Soft-HGRNs: soft hierarchical graph recurrent networks for multi-agent partially observable environments
Author(s):Yixiang REN, Zhenhui YE, Yining CHEN, Xiaohong JIANG, Guanghua SONG  Clicked:1648  Download:1604  Cited:0  <Full Text>  <PPT> 234
Frontiers of Information Technology & Electronic Engineering  2023 Vol.24 No.1 P.117-130  DOI:10.1631/FITEE.2200073
5Transformer in reinforcement learning for decision-making: a survey
Author(s):Weilin YUAN, Jiaxing CHEN, Shaofei CHEN, Dawei FENG,Zhenzhen HU, Peng LI, Weiwei ZHAO  Clicked:208  Download:303  Cited:0  <Full Text>
Frontiers of Information Technology & Electronic Engineering  In Press    DOI:
6Multiagent evaluation for energy management by Practically scaling α-rank
Author(s):Yiyun SUN, Senlin ZHANG, Meiqin LIU, Ronghao ZHENG,Shanling DONG, Xuguang LAN  Clicked:122  Download:87  Cited:0  <Full Text>
Frontiers of Information Technology & Electronic Engineering  In Press    DOI:
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