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Air-M: A Visual Reality Many-Agent Reinforcement Learning Platform for Large-Scale Aerial Unmanned System.

, , , и . IROS, стр. 5598-5605. (2023)

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Huili Shi

Lei Shi

Zhanjun Shi

Renhu Shi

Jian Shi

 

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TRAMESINO: Traffic Memory System for Intelligent Optimization of Road Traffic Control., , , , , , , , и . AALTD@ECML/PKDD, том 13114 из Lecture Notes in Computer Science, стр. 88-103. Springer, (2021)An LSTM-Based Autonomous Driving Model Using Waymo Open Dataset., , , и . CoRR, (2020)Hierarchical Consensus-Based Multi-Agent Reinforcement Learning for Multi-Robot Cooperation Tasks., , , , , и . CoRR, (2024)ESP: Exploiting Symmetry Prior for Multi-Agent Reinforcement Learning., , , , , и . CoRR, (2023)A Physics-Informed Deep Learning Paradigm for Car-Following Models., , и . CoRR, (2020)OBELISC: Oscillator-Based Modelling and Control Using Efficient Neural Learning for Intelligent Road Traffic Signal Calculation., , , , , , , , и . ECML/PKDD (4), том 12978 из Lecture Notes in Computer Science, стр. 437-452. Springer, (2021)Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models., , и . AAAI, стр. 540-547. AAAI Press, (2021)Generating Synthetic Passenger Data through Joint Traffic-Passenger Modeling and Simulation., , и . ITSC, стр. 3397-3402. IEEE, (2018)A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation., , , , и . IEEE Trans. Intell. Transp. Syst., 23 (8): 11688-11698 (2022)A Physics-Informed Deep Learning Paradigm for Traffic State Estimation and Fundamental Diagram Discovery., , , , и . CoRR, (2021)