Abstract:Predicting mobile users' trajectories accurately is essential for improving the performance of wireless networks and autonomous systems. In this paper, we tackle the problem of trajectory prediction in a multi-agent scenario where the social interaction among users is taken into consideration. We propose Intra-Cluster Reinforced Social Transformer (INTRAFORCE), a novel system to design and train Social-Transformer neural networks that learn the spatio-temporal interactions among neighboring mobile users and pr… Show more
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