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City metro network expansion based on multi-objective reinforcement learning Journal article
Zhang, Liqing, U, Leong Hou, Ni, Shaoquan, Chen, Dingjun, Li, Zhenning, Wang, Wenxian, Xian, Weizhi. City metro network expansion based on multi-objective reinforcement learning[J]. Transportation Research Part C: Emerging Technologies, 2024, 169, 104880.
Authors:  Zhang, Liqing;  U, Leong Hou;  Ni, Shaoquan;  Chen, Dingjun;  Li, Zhenning; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:7.6/9.6 | Submit date：2024/11/05
Actor-critic Network  Metro Expansion  Reinforcement Learning  
Utilizing Deep Reinforcement Learning for High-Voltage Distribution Network Expansion Planning Conference paper
Ou, Zhongxi, Zhang, Liang, Zhao, Xiaoyan, Lan, Wei, Liu, Dundun, Liu, Weifeng. Utilizing Deep Reinforcement Learning for High-Voltage Distribution Network Expansion Planning[C]:Institute of Electrical and Electronics Engineers Inc., 2024, 725-730.
Authors:  Ou, Zhongxi;  Zhang, Liang;  Zhao, Xiaoyan;  Lan, Wei;  Liu, Dundun; et al.
Favorite | TC[Scopus]:0 | Submit date：2024/09/03
Advantage Actor-critic  Deep Reinforcement Learning  Distribution Network Expansion  Markov Decision Process  
Joint Resource Overbooking and Container Scheduling in Edge Computing Journal article
Tang Zhiqing, Mou Fangyi, Lou Jiong, Jia Weijia, Wu Yuan, Zhao Wei. Joint Resource Overbooking and Container Scheduling in Edge Computing[J]. IEEE Transactions on Mobile Computing, 2024, 23(12), 10903 - 10917.
Authors:  Tang Zhiqing;  Mou Fangyi;  Lou Jiong;  Jia Weijia;  Wu Yuan; et al.
Favorite | TC[Scopus]:1  IF:7.7/6.5 | Submit date：2024/05/16
Container Scheduling  Edge Computing  Resource Overbooking  Soft Actor-critic Reinforcement Learning  
Deep Reinforcement Learning-based RAN Slicing for UL/DL Decoupled Cellular V2X Journal article
Yu, Kai, Zhou, Haibo, Tang, Zhixuan, Shen, Xuemin, Hou, Fen. Deep Reinforcement Learning-based RAN Slicing for UL/DL Decoupled Cellular V2X[J]. IEEE Transactions on Wireless Communications, 2022, 21(5).
Authors:  Yu, Kai;  Zhou, Haibo;  Tang, Zhixuan;  Shen, Xuemin;  Hou, Fen
Favorite | TC[WOS]:23 TC[Scopus]:28  IF:8.9/8.6 | Submit date：2022/05/13
Ran Slicing  Decoupled Access  Soft Actor-critic  Reinforcement Learning  
Sparse online kernelized actor-critic Learning in reproducing kernel Hilbert space Journal article
Yang, Yongliang, Zhu, Hufei, Zhang, Qichao, Zhao, Bo, Li, Zhenning, Wunsch, Donald C.. Sparse online kernelized actor-critic Learning in reproducing kernel Hilbert space[J]. Artificial Intelligence Review, 2021, 55, 23-58.
Authors:  Yang, Yongliang;  Zhu, Hufei;  Zhang, Qichao;  Zhao, Bo;  Li, Zhenning; et al.
Favorite | TC[WOS]:23 TC[Scopus]:22  IF:10.7/11.7 | Submit date：2022/02/21
Actor-critic Learning  Non-parametric Learning  Online Sparsification  Reproducing Kernel Hilbert Space  Value Function Approximation  
Robust Actor-Critic Learning for Continuous-Time Nonlinear Systems with Unmodeled Dynamics Journal article
Yang,Yongliang, Gao,Weinan, Modares,Hamidreza, Xu,Cheng Zhong. Robust Actor-Critic Learning for Continuous-Time Nonlinear Systems with Unmodeled Dynamics[J]. IEEE Transactions on Fuzzy Systems, 2021.
Authors:  Yang,Yongliang;  Gao,Weinan;  Modares,Hamidreza;  Xu,Cheng Zhong
Favorite | TC[WOS]:98 TC[Scopus]:113  IF:10.7/9.7 | Submit date：2021/05/31
Fuzzy Logic  Heuristic Algorithms  Input-to-state Stability  Nonlinear Dynamical Systems  Optimal Control  Optimal Control  Power System Dynamics  Robust Actor-critic Learning  Stability Criteria  Uncertainty  Unmodeled Dynamics  
Adaptive tracking control of surface vessel using optimized backstepping technique Journal article
Wen,Guoxing, Ge,Shuzhi Sam, Chen,C. L.Philip, Tu,Fangwen, Wang,Shengnan. Adaptive tracking control of surface vessel using optimized backstepping technique[J]. IEEE Transactions on Cybernetics, 2019, 49(9), 3420-3431.
Authors:  Wen,Guoxing;  Ge,Shuzhi Sam;  Chen,C. L.Philip;  Tu,Fangwen;  Wang,Shengnan
Favorite | TC[WOS]:164 TC[Scopus]:177  IF:9.4/10.3 | Submit date：2021/03/09
Actor-critic Architecture  Lyapunov Stability  Optimized Backstepping (Ob)  Reinforcement Learning (Rl)  Surface Vessel  
Optimized Multi-Agent Formation Control Based on an Identifier-Actor--Critic Reinforcement Learning Algorithm Journal article
Wen, Guoxing, Chen, C. L. Philip, Feng, Jun, Zhou, Ning. Optimized Multi-Agent Formation Control Based on an Identifier-Actor--Critic Reinforcement Learning Algorithm[J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26(5), 2719-2731.
Authors:  Wen, Guoxing;  Chen, C. L. Philip;  Feng, Jun;  Zhou, Ning
View | Adobe PDF | Favorite | TC[WOS]:130 TC[Scopus]:139  IF:10.7/9.7 | Submit date：2018/10/30
Fuzzy Logic Systems (Flss)  Identifier-actor-critic Architecture  Multi-agent Formation  Optimized Formation Control  Reinforcement Learning (Rl)  
Optimized Multi-Agent Formation Control Based on an Identifier-Actor-Critic Reinforcement Learning Algorithm Journal article
Wen G., Chen C.L.P., Feng J., Zhou N.. Optimized Multi-Agent Formation Control Based on an Identifier-Actor-Critic Reinforcement Learning Algorithm[J]. IEEE Transactions on Fuzzy Systems, 2018, 26(5), 2719-2731.
Authors:  Wen G.;  Chen C.L.P.;  Feng J.;  Zhou N.
Favorite | TC[WOS]:130 TC[Scopus]:139 | Submit date：2019/02/11
Fuzzy Logic Systems (Flss)  Identifier-actor-critic Architecture  Multi-agent Formation  Optimized Formation Control  Reinforcement Learning (Rl)