2 citations · 2 across the 3 of their papers we have counts for
4 papers
Progression Cognition Reinforcement Learning with Prioritized Experience for Multi-Vehicle Pursuit
Xinhang Li, Yiying Yang, Zheng Yuan +6
Multi-vehicle pursuit (MVP) such as autonomous police vehicles pursuing suspects is important but very challenging due to its mission and safety critical nature. While multi-agent…
Graded-Q Reinforcement Learning with Information-Enhanced State Encoder for Hierarchical Collaborative Multi-Vehicle Pursuit
Yiying Yang, Xinhang Li, Zheng Yuan +3
The multi-vehicle pursuit (MVP), as a problem abstracted from various real-world scenarios, is becoming a hot research topic in Intelligent Transportation System (ITS). The combina…
An Opponent-Aware Reinforcement Learning Method for Team-to-Team Multi-Vehicle Pursuit via Maximizing Mutual Information Indicator
Qinwen Wang, Xinhang Li, Zheng Yuan +3
The pursuit-evasion game in Smart City brings a profound impact on the Multi-vehicle Pursuit (MVP) problem, when police cars cooperatively pursue suspected vehicles. Existing studi…
A Credibility-aware Swarm-Federated Deep Learning Framework in Internet of Vehicles
Zhe Wang, Xinhang Li, Tianhao Wu +2
Federated Deep Learning (FDL) is helping to realize distributed machine learning in the Internet of Vehicles (IoV). However, FDL's global model needs multiple clients to upload lea…