Suchergebnisse - "multi agent deep deterministic policy gradient algorithm"

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  1. 1

    Grid-area coordinated load frequency control strategy using large-scale multi-agent deep reinforcement learning von Li, Jiawen, Geng, Jian, Yu, Tao

    ISSN: 2352-4847, 2352-4847
    Veröffentlicht: Elsevier Ltd 01.11.2022
    Veröffentlicht in Energy reports (01.11.2022)
    “… In order to enable full participation of high-performance units controlled by different dispatching centers in the performance-based frequency regulation …”
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    Journal Article
  2. 2

    Improved Multi-Agent Deep Deterministic Policy Gradient for Path Planning-Based Crowd Simulation von Zheng, Shangfei, Liu, Hong

    ISSN: 2169-3536, 2169-3536
    Veröffentlicht: Piscataway IEEE 2019
    Veröffentlicht in IEEE access (2019)
    “… Deep reinforcement learning (DRL) has been proved to be more suitable than reinforcement learning for path planning in large-scale scenarios. In order to more …”
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    Journal Article
  3. 3

    基于多智能体深度强化学习的无人艇集群博弈对抗研究 von 于长东, 刘新阳, 陈聪, 刘殿勇, 梁霄

    ISSN: 2096-3920
    Veröffentlicht: 大连海事大学船舶与海洋工程学院,辽宁大连, 116026 01.02.2024
    Veröffentlicht in 水下无人系统学报 (01.02.2024)
    “… TJ630%U664.82; 基于未来现代化海上作战背景,提出了利用多智能体深度强化学习方案来完成无人艇群博弈对抗中的协同围捕任务.首先,根据不同的作战模式和应用场景,提出基于分 …”
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  4. 4

    Research on Game Confrontation of Unmanned Surface Vehicles Swarm Based on Multi-Agent Deep Reinforcement Learning von Changdong YU, Xinyang LIU, Cong CHEN, Dianyong LIU, Xiao LIANG

    ISSN: 2096-3920
    Veröffentlicht: Science Press (China) 01.02.2024
    Veröffentlicht in 水下无人系统学报 (01.02.2024)
    “… Based on the background of future modern maritime combats, a multi-agent deep reinforcement learning scheme was proposed to complete the cooperative round-up …”
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  5. 5

    Research on Bidding Strategy of Thermal Power Companies in Electricity Market Based on Multi-Agent Deep Deterministic Policy Gradient von Liu, Dunnan, Gao, Yuan, Wang, Weiye, Dong, Zhixin

    ISSN: 2169-3536, 2169-3536
    Veröffentlicht: Piscataway IEEE 2021
    Veröffentlicht in IEEE access (2021)
    “… With the continuous improvement of new energy penetration in the power system, the price of the spot market of power frequently fluctuates greatly, which …”
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  6. 6

    Large-scale deep reinforcement learning method for energy management of power supply units considering regulation mileage payment von Qian, Ting, Yang, Cheng

    ISSN: 2296-598X, 2296-598X
    Veröffentlicht: Frontiers Media S.A 14.03.2024
    Veröffentlicht in Frontiers in energy research (14.03.2024)
    “… To improve automatic generation control (AGC) performance and reduce the wastage of regulation resources in interconnected grids including high-proportion …”
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    Journal Article
  7. 7

    A multi-agent deep reinforcement learning-based “Octopus” cooperative load frequency control for an interconnected grid with various renewable units von Li, Jiawen, Yu, Tao, Cui, Haoyang

    ISSN: 2213-1388
    Veröffentlicht: Elsevier Ltd 01.06.2022
    Veröffentlicht in Sustainable energy technologies and assessments (01.06.2022)
    “… •A data-driven “octopus” cooperative load frequency control (OC-LFC) method for an interconnected power system is proposed.•An TED-MADDPG algorithm is proposed …”
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  8. 8

    AUV Swarm Confrontation Search Method Based on the MADDPG Algorithm von An, Ruiqi, Li, Le, Bai, Miao, Zhang, Pu, Guo, Zhaozhi, Zuo, Ri

    ISSN: 1948-9447
    Veröffentlicht: IEEE 16.05.2025
    Veröffentlicht in Chinese Control and Decision Conference (16.05.2025)
    “… In this paper, an Autonomous Underwater Vehicle (AUV) swarm confrontation search method based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) …”
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