… smart cooperative vehicular networks were discussed from the aspects of the … : a reinforcement
learning approach for multipath TCP congestion control in heterogeneous networks[J]. …

… intelligent vehicles, reinforcement learning and optimal control, … congestion control in cellular
vehicle-to-everything networks. … DSRC-based vehicle network communication performance …

… in vehicular transportation network”, “Machine learning for traffic sign recognition”, “Grand
cooperative driving … This dissertation focuses on wireless channel congestion and biased …

… vehicular networks with heavy traffic environment, a channel … 机器学习(machine
learning,ML)理论中的MAB(multi1armed … outperform generic no1regret learning in congestion …

… In this context, envision a reliable distributed cloud models to … space is allotted in the
base station itself. part of the process … processing, the Deep Reinforcement Learning [DRL] …

… , travel cost, awareness, and congestion. The awareness of QoS … There exist several issues
in the vehicular networks of ITS, … Distributed reinforcement learning approach for vehicular ad …

… for congested vehicular networks[C]//Proceedings of 2020 … in vehicular networks: a proactive
deep reinforcement learning … Deep reinforcement learning for cooperative content caching …

… ,inference-aware multi-agent deep reinforcement learning) [21] 方法引入… Channel access
optimization with adaptive congestion … Cooperative content delivery in vehicular networks with …

… of artificial intelligence and machine learning into energy tech… prominent, reducing the
congestion effect caused by … to team cooperation, while the psychological distance from a …