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cs.NI2026
Multi-Agent DRL for Multi-Objective Twin Migration Routing with Workload Prediction in 6G-enabled IoV
Peng Yin, Wentao Liang, Jinbo Wen +3
Sixth Generation (6G)-enabled Internet of Vehicles (IoV) facilitates efficient data synchronization through ultra-fast bandwidth and high-density connectivity, enabling the emergen…
cs.NI2025
Efficient Twin Migration in Vehicular Metaverses: Multi-Agent Split Deep Reinforcement Learning with Spatio-Temporal Trajectory Generation
Junlong Chen, Jiawen Kang, Minrui Xu +5
Vehicle Twins (VTs) as digital representations of vehicles can provide users with immersive experiences in vehicular metaverse applications, e.g., Augmented Reality (AR) navigation…
cs.NI2024
Diffusion-based Auction Mechanism for Efficient Resource Management in 6G-enabled Vehicular Metaverses
Jiawen Kang, Yongju Tong, Yue Zhong +5
The rise of 6G-enable Vehicular Metaverses is transforming the automotive industry by integrating immersive, real-time vehicular services through ultra-low latency and high bandwid…