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Results for deep reinforcement learning

Publications & Outputs

  1. Deep-Deterministic-Policy-Gradient-Based Task Offloading With Optimized K-Means in Edge-Computing-Enabled IoMT Cyber-Physical Systems

    Yang, C., Xu, X., Bilal, M., Wen, Y. & Huang, T., 1/12/2023, In: IEEE Systems Journal. 17, 4, p. 5195 - 5206 12 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  2. Online Service Migration in Mobile Edge with Incomplete System Information: A Deep Recurrent Actor-Critic Learning Approach

    Wang, J., Hu, J., Min, G., Ni, Q. & El-Ghazawi, T., 1/11/2023, In: IEEE Transactions on Mobile Computing. 22, 11, p. 6663-6675 13 p., 11.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  3. Computation Offloading for Energy and Delay Trade-Offs With Traffic Flow Prediction in Edge Computing-Enabled IoV

    Xu, X., Yang, C., Bilal, M., Li, W. & Wang, H., 23/11/2022, (E-pub ahead of print) In: IEEE Transactions on Intelligent Transportation Systems. p. 1-11 11 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  4. Dynamic Edge Computation Offloading for Internet of Vehicles With Deep Reinforcement Learning

    Yao, L., Xu, X., Bilal, M. & Wang, H., 6/06/2022, (E-pub ahead of print) In: IEEE Transactions on Intelligent Transportation Systems. p. 1-9 9 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review

  5. CoPace: Edge Computation Offloading and Caching for Self-Driving with Deep Reinforcement Learning

    Tian, H., Xu, X., Qi, L., Zhang, X., Dou, W., Yu, S. & Ni, Q., 31/12/2021, In: IEEE Transactions on Vehicular Technology. 70, 12, p. 13281-13293 13 p.

    Research output: Contribution to Journal/MagazineJournal articlepeer-review