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Team-wise effective communication in multi-agent reinforcement learning Journal article
Yang, Ming, Zhao, Kaiyan, Wang, Yiming, Dong, Renzhi, Du, Yali, Liu, Furui, Zhou, Mingliang, U, Leong Hou. Team-wise effective communication in multi-agent reinforcement learning[J]. Autonomous Agents and Multi-Agent Systems, 2024, 38(2), 36.
Authors:  Yang, Ming;  Zhao, Kaiyan;  Wang, Yiming;  Dong, Renzhi;  Du, Yali; et al.
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:2.0/2.1 | Submit date：2024/08/05
Communication  Competition  Cooperation  Multi-agent System  Reinforcement Learning  
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  
Adaptive Tie-line Power Smoothing with Renewable Generation Based on Risk-aware Reinforcement Learning Journal article
Peipei Yu, Hongcai Zhang, Yonghua Song. Adaptive Tie-line Power Smoothing with Renewable Generation Based on Risk-aware Reinforcement Learning[J]. IEEE Transactions on Power Systems, 2024, 39(6), 6819-6832.
Authors:  Peipei Yu;  Hongcai Zhang;  Yonghua Song
Favorite | TC[WOS]:2 TC[Scopus]:4  IF:6.5/7.4 | Submit date：2024/04/24
Tie-line Power Smoothing  Demand Response  Renewable Generation  Risk-aware Reinforcement Learning  
A multi-stage stochastic dispatching method for electricity‑hydrogen integrated energy systems driven by model and data Journal article
Yang, Zhixue, Ren, Zhouyang, Li, Hui, Sun, Zhiyuan, Feng, Jianbing, Xia, Weiyi. A multi-stage stochastic dispatching method for electricity‑hydrogen integrated energy systems driven by model and data[J]. Applied Energy, 2024, 371, 123668.
Authors:  Yang, Zhixue;  Ren, Zhouyang;  Li, Hui;  Sun, Zhiyuan;  Feng, Jianbing; et al.
Favorite | TC[WOS]:4 TC[Scopus]:12  IF:10.1/10.4 | Submit date：2024/07/04
Chance-constrained  Electricity‑hydrogen Integrated Energy Systems  Hydrogen Energy  Multi-agent Deep Reinforcement Learning  Uncertainty  
Attention-Based SIC Ordering and Power Allocation for Non-Orthogonal Multiple Access Networks Journal article
Huang, Liang, Zhu, Bincheng, Nan, Runkai, Chi, Kaikai, Wu, Yuan. Attention-Based SIC Ordering and Power Allocation for Non-Orthogonal Multiple Access Networks[J]. IEEE Transactions on Mobile Computing, 2024.
Authors:  Huang, Liang;  Zhu, Bincheng;  Nan, Runkai;  Chi, Kaikai;  Wu, Yuan
Favorite | TC[Scopus]:0  IF:7.7/6.5 | Submit date：2024/11/05
Non-orthogonal Multiple Access (Noma)  Successive Interference Cancellation (Sic)  Deep Reinforcement Learning (Drl)  Resource Allocation  
Offline DRL for Price-Based Demand Response: Learning From Suboptimal Data and Beyond Journal article
Tao Qian, Zeyu Liang, Chengcheng Shao, Hongcai Zhang, Qinran Hu, Zaijun Wu. Offline DRL for Price-Based Demand Response: Learning From Suboptimal Data and Beyond[J]. IEEE Transactions on Smart Grid, 2024, 15(5), 4618-4635.
Authors:  Tao Qian;  Zeyu Liang;  Chengcheng Shao;  Hongcai Zhang;  Qinran Hu; et al.
Favorite | TC[WOS]:3 TC[Scopus]:5  IF:8.6/9.6 | Submit date：2024/04/24
Demand Response  Deep Reinforcement Learning  Offline Learning  Suboptimal Data  Uncertainty  
RL-CWtrans Net: multimodal swimming coaching driven via robot vision Journal article
Wang, Guanlin. RL-CWtrans Net: multimodal swimming coaching driven via robot vision[J]. Frontiers in Neurorobotics, 2024, 18, 1439188.
Authors:  Wang, Guanlin
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:2.6/3.1 | Submit date：2024/09/03
Artificial Neural Networks  Clip  Feature Extraction  Multimodal Robot  Reinforcement Learning  Robot Vision  Swin-transformer  
Deep Reinforcement Learning for Integrated Sensing and Communication in RIS-assisted 6G V2X System Journal article
Long, Xudong, Zhao, Yubin, Wu, Huaming, Xu, Cheng Zhong. Deep Reinforcement Learning for Integrated Sensing and Communication in RIS-assisted 6G V2X System[J]. IEEE Internet of Things Journal, 2024.
Authors:  Long, Xudong;  Zhao, Yubin;  Wu, Huaming;  Xu, Cheng Zhong
Favorite | TC[Scopus]:0  IF:8.2/9.0 | Submit date：2024/10/10
6g Mobile Communication  6g V2x  Accuracy  Array Signal Processing  Channel Models  Deep Reinforcement Learning  Fisher Information Matrix  Integrated Sensing And Communication  Isac  Optimization  Reconfigurable Intelligent Surface  Vehicle-to-everything  
DRPC: Distributed Reinforcement Learning Approach for Scalable Resource Provisioning in Container-based Clusters Journal article
Bai, Haoyu, Xu, Minxian, Ye, Kejiang, Buyya, Rajkumar, Xu, Chengzhong. DRPC: Distributed Reinforcement Learning Approach for Scalable Resource Provisioning in Container-based Clusters[J]. IEEE TRANSACTIONS ON SERVICE COMPUTING, 2024, 1-12.
Authors:  Bai, Haoyu;  Xu, Minxian;  Ye, Kejiang;  Buyya, Rajkumar;  Xu, Chengzhong
Favorite | TC[Scopus]:0  IF:5.5/5.9 | Submit date：2024/08/05
Cloud Computing  Distributed Resources Management  Reinforcement Learning  Kubernetes  Microservice  
Deterministic Policy Gradient based Reinforcement Learning for Current Control of Hybrid Active Power Filter Conference paper
Gong, Cheng, Leong, Chio Hong, Lam, Chi Seng. Deterministic Policy Gradient based Reinforcement Learning for Current Control of Hybrid Active Power Filter[C]:Institute of Electrical and Electronics Engineers Inc., 2024.
Authors:  Gong, Cheng;  Leong, Chio Hong;  Lam, Chi Seng
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2024/08/05
Deterministic Policy Gradient  Hybrid Active Power Filter  Power Quality  Reinforcement Learning