Federated Digital Twins: A Scheduling Approach Based on Temporal Graph Neural Network and Deep Reinforcement Learning by Young-Jin Kim, Hanjin Kim, Beomsu Ha, Won-Tae Kim

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Coordinated Volt/VAR Control in Distribution Networks Considering Demand Response via Safe Deep Reinforcement Learning by Dong Hua, Fei Peng, Suisheng Liu, Qinglin Lin, Jiahui Fan, Qian Li

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Hybrid learning strategies: integrating supervised and reinforcement techniques for railway wheel wear management with limited measurement data by Jessada Sresakoolchai, Chayut Ngamkhanong, Sakdirat Kaewunruen

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Exploration Degree Bias: The Hidden Influence of Node Degree in Graph Neural Network-Based Reinforcement Learning by Peter Tarabek, David Matis

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Multi-tenant computing network resource allocation algorithm based on deep reinforcement learning by HU Yuxiang, FENG Xu, DONG Yongji, HE Mengyang, ZHUANG Lei, SONG Yanrui

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A Data-Intelligence-Driven Digital Twin Framework for Improving Sustainability in Logistics by Ibrahim Abdullahi, Hadi Larijani, Dimitrios Liarokapis, James Paterson, David Jones, Stewart Murray

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HEVERL – Viewport Estimation Using Reinforcement Learning for 360-degree Video Streaming by Nguyen Viet Hung, Pham Tien Dat, Nguyen Tan, Nguyen Anh Quan, Le Thi Huyen Trang, Le Mai Nam

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Deep reinforcement learning for time-critical wilderness search and rescue using drones by Jan-Hendrik Ewers, David Anderson, Douglas Thomson

Subjects: “…reinforcement learning…”
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Crowding distance and IGD-driven grey wolf reinforcement learning approach for multi-objective agile earth observation satellite scheduling by He Wang, Weiquan Huang, Sindri Magnússon, Tony Lindgren, Chen Chen, Junyu Wu, Yanjie Song

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Adaptive Cruise Control Utilizing Noisy Multi-Leader Measurements: A Learning-Based Approach by Ying-Chuan Ni, Victor L. Knoop, Julian F. P. Kooij, Bart van Arem

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Optimization Method of Underwater Flapping Foil Propulsion Performance Based on Gaussian Process Regression and Deep Reinforcement Learning by YANG Yinghe, WEI Handi, FAN Dixia, LI Ang

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Bias-free policy evaluation in the discrete-time adaptive linear quadratic optimal control in the presence of stochastic disturbances by Vina Putri Virgiani, Natsuki Ishigaki, Shiro Masuda

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Two-stage deep reinforcement learning method for agile optical satellite scheduling problem by Zheng Liu, Wei Xiong, Zhuoya Jia, Chi Han

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Deep Reinforcemnet Learning for Robust Beamforming in Integrated Sensing, Communication and Power Transmission Systems by Chenfei Xie, Yue Xiu, Songjie Yang, Qilong Miao, Lu Chen, Yong Gao, Zhongpei Zhang

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Swarm Confrontation Algorithm for UGV Swarm with Quantity Advantage by a Novel MSRM-MAPOCA Training Method by Huanli Gao, Chongming Zhao, Xinghe Yu, Shuangfei Ren, He Cai

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Cloud-edge hybrid deep learning framework for scalable IoT resource optimization by Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani

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Voltage-driven autonomous cooperative control of EHLs for load stabilization by Bing Qi, Rui Liu, Deying Zhang, Zhuoqun Wang, Qi Qi

Subjects: “…Multi-agent deep reinforcement learning…”
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Combining Software-Defined and Delay-Tolerant Networking Concepts With Deep Reinforcement Learning Technology to Enhance Vehicular Networks by Olivia Nakayima, Mostafa I. Soliman, Kazunori Ueda, Samir A. Elsagheer Mohamed

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Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

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Path Planning for Fully Autonomous UAVs-A Taxonomic Review and Future Perspectives by Geeta Sharma, Sanjeev Jain, Radhe Shyam Sharma

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