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    Integrating big data analytics in autonomous driving: An unsupervised hierarchical reinforcement learning approach

    Mao, Zhiqi / Liu, Yang / Qu, Xiaobo | Elsevier | 2024
    Schlagwörter: Reinforcement learning , Deep learning , Unsupervised skill learning

    Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform

    Liu, Yang / Wu, Fanyou / Lyu, Cheng et al. | Elsevier | 2022
    Schlagwörter: Deep reinforcement learning

    Station-keeping for high-altitude balloon with reinforcement learning

    Xu, Ziyuan / Liu, Yang / Du, Huafei et al. | Elsevier | 2022
    Schlagwörter: Dueling double deep Q learning network , Reinforcement learning

    A feature pseudo-fusion method for intelligent fault diagnosis of electro-hydraulic switch machine inspired by contrastive learning

    Wen, Weigang / Liu, Yang / Bai, Yihao et al. | SAGE Publications | 2023
    Schlagwörter: contrastive learning

    Harnessing the power of Machine learning for AIS Data-Driven maritime Research: A comprehensive review

    Yang, Ying / Liu, Yang / Li, Guorong et al. | Elsevier | 2024
    Schlagwörter: Machine learning

    Prediction of Traffic Incident Duration Using Clustering-Based Ensemble Learning Method

    Zhao, Hui / Gunardi, Willy / Liu, Yang et al. | ASCE | 2022
    Schlagwörter: Ensemble learning

    Deep reinforcement learning for dynamic incident-responsive traffic information dissemination

    Xie, Jiaohong / Yang, Zhenyu / Lai, Xiongfei et al. | Elsevier | 2022
    Schlagwörter: Deep reinforcement learning

    Deep reinforcement learning-based safe interaction for industrial human-robot collaboration using intrinsic reward function

    Freier Zugriff
    Liu, Quan / Liu, Zhihao / Xiong, Bo et al. | BASE | 2021
    Schlagwörter: Deep reinforcement learning

    Stochastic one-way carsharing systems with dynamic relocation incentives through preference learning

    Liu, Yang / Xie, Jiaohong / Chen, Nan | Elsevier | 2022
    Schlagwörter: User preference learning

    Gauss mixture hidden Markov model to characterise and model discretionary lane-change behaviours for autonomous vehicles

    Freier Zugriff
    Jin, Hao / Duan, Chunguang / Liu, Yang et al. | IET | 2020
    Schlagwörter: learning (artificial intelligence)

      Gauss mixture hidden Markov model to characterise and model discretionary lane‐change behaviours for autonomous vehicles

      Freier Zugriff
      Jin, Hao / Duan, Chunguang / Liu, Yang et al. | Wiley | 2020
      Schlagwörter: learning (artificial intelligence)

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