Výsledky vyhledávání - Distributed multi-agent deep deterministic policy gradient algorithm

Distributed Deep Deterministic Policy Gradient for Power Allocation Control in D2D-Based V2V Communications Autor Nguyen, Khoi Khac, Duong, Trung Q., Vien, Ngo Anh, Le-Khac, Nhien-An, Nguyen, Long D.

“… In this paper, we present two novel approaches based on deep deterministic policy gradient algorithm, namely "distributed…”
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A multi-agent deep reinforcement learning-based “Octopus” cooperative load frequency control for an interconnected grid with various renewable units Autor Li, Jiawen, Yu, Tao, Cui, Haoyang

“…•An TED-MADDPG algorithm is proposed which improves the robustness of the framework.•The controller and power distributor in each area are regarded as independent agents…”
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A Dynamic Deceptive Defense Framework for Zero-Day Attacks in IIoT: Integrating Stackelberg Game and Multi-Agent Distributed Deep Deterministic Policy Gradient Autor Shen, Shigen, Ji, Xiaojun, Liu, Yimeng

“… To address this critical challenge, this paper proposes a dynamic defense framework named Zero-day-aware Stackelberg Game-based Multi-Agent Distributed Deep Deterministic Policy Gradient (ZSG-MAD3PG…”
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Multi-Agent DRL for Air-to-Ground Communication Planning in UAV-Enabled IoT Networks Autor Qureshi, Khalid Ibrahim, Lu, Bingxian, Lu, Cheng, Lodhi, Muhammad Ali, Wang, Lei

“…In this paper, we present a novel method to enhance the sum-rate effectiveness in full-duplex unmanned aerial vehicle (UAV)-assisted communication networks…”
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Multi-Agent Reinforcement Learning using the Deep Distributed Distributional Deterministic Policy Gradients Algorithm Autor Farag, Wael

“…In this paper, the Deep Distributed Distributional Deterministic Policy Gradients (D4PG…”
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3DPG: Distributed Deep Deterministic Policy Gradient Algorithms for Networked Multi-Agent Systems Autor Redder, Adrian, Ramaswamy, Arunselvan, Karl, Holger

“…We present Distributed Deep Deterministic Policy Gradient (3DPG), a multi-agent actor-critic (MAAC…”
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Optimal demand response based dynamic pricing strategy via Multi-Agent Federated Twin Delayed Deep Deterministic policy gradient algorithm Autor Ma, Haining, Zhang, Huifeng, Tian, Ding, Yue, Dong, Hancke, Gerhard P.

“…(TD3) policy gradient algorithm is proposed to construct a federated learning mechanism among multi agents…”
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Friend-or-Foe Deep Deterministic Policy Gradient Autor Jiang, Hao, Shi, Dianxi, Xue, Chao, Wang, Yajie, Wang, Gongju, Zhang, Yongjun

“… To address this problem, we propose a novel algorithm termed Friend-or-Foe Deep Deterministic Policy Gradient (FD2PG…”
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Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learning Autor Harrold, Daniel J.B., Cao, Jun, Fan, Zhong

“… For this, the algorithm deep deterministic policy gradients (DDPG) and multi-agent DDPG (MADDPG) are used to compare…”
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Distributed MA‐IDDPG‐OLSR based stable routing protocol for unmanned aerial vehicle ad‐hoc network Autor Zeng, Youjun, Zhou, Jie, Liu, Youjiang, Cao, Tao, Yang, Dalong, Liu, Yu, Shi, Xianhua

“…‐agent independent deep deterministic policy gradient‐OLSR (MA‐IDDPG‐OLSR) routing protocol based on distributed multi…”
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Multi-Agent DDPG-Based Multi-Device Charging Scheduling for IIoT Smart Grids Autor Zeng, Haiyong, Huang, Yuanyan, Zhan, Kaijie, Yu, Zichao, Zhu, Hongyan, Li, Fangyan

“… proposes a dynamic charging scheduling algorithm for EVs based on Multi-Agent Deep Deterministic Policy Gradient (MADDPG…”
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Multi-agent learning based UAV-assisted MEC-NOMA for cellular offloading in Internet of Things Autor Wu, Guowei, Chen, Guifen, Gu, Xinglong

“…Unmanned Aerial Vehicle (UAV)-assisted Mobile Edge Computing (MEC) is emerging as a viable technology for computation-intensive and latency-critical jobs in…”
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Research on Game Confrontation of Unmanned Surface Vehicles Swarm Based on Multi-Agent Deep Reinforcement Learning Autor Changdong YU, Xinyang LIU, Cong CHEN, Dianyong LIU, Xiao LIANG

“… of unmanned surface vehicles (USVs). First, based on different combat modes and application scenarios, a multi-agent deep deterministic policy gradient algorithm based on distributed execution was determined, and its principle was introduced…”
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Joint Multi-objective Optimization for Radio Access Network Slicing Using Multi-agent Deep Reinforcement Learning Autor Zhou, Guorong, Zhao, Liqiang, Zheng, Gan, Xie, Zhijie, Song, Shenghui, Chen, Kwang-Cheng

“…)' deployment, and sub-channel and power allocation. An improved multi-agent deep deterministic policy gradient (IMADDPG…”
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Optimal Bi-Level Bidding and Dispatching Strategy Between Active Distribution Network and Virtual Alliances Using Distributed Robust Multi-Agent Deep Reinforcement Learning Autor Zhu, Ziqing, Chan, Ka Wing, Xia, Shiwei, Bu, Siqi

“…, and then re-formulated as a Markov Decision Process to be solved by a new Distributed Robust Multi-Agent Deep Deterministic Policy Gradient algorithm based on the concept of robust Nash equilibrium (RNE…”
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Multi-agent distributed deep reinforcement learning algorithm in cloud environment Autor Gong, Shuai, Cheng, Hang, Cao, Wanwan, Yu, Dongbo, Chen, Chao

“… not only has a slow convergence speed, but also the stability of the algorithm cannot be guaranteed. In this paper, a multi-agent distributed deep deterministic policy…”
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Vehicle Edge Computing Task Offloading Strategy Based on Multi-Agent Deep Reinforcement Learning Autor Bo, Jianxiong, Zhao, Xu

“…With the rapid advancement of autonomous driving technology, the volume of data generated by vehicle sensors is growing exponentially. Due to spatial…”
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Post-Disaster Generation Dispatching for Enhanced Resilience: A Multi-Agent Deep Deterministic Policy Gradient Learning Approach Autor Abdelmalak, Michael, Hosseinpour, Hadis, Hotchkiss, Eliza, Ben-Idris, Mohammed

“… for real-time control applications. In this paper, a multi-agent deep deterministic policy gradient learning algorithm is developed to dispatch distributed generators after an extreme event…”
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Multiagent Deep-Reinforcement-Learning-Based Resource Allocation for Heterogeneous QoS Guarantees for Vehicular Networks Autor Tian, Jie, Liu, Qianqian, Zhang, Haixia, Wu, Dalei

“… In this article, a multi-agent deep reinforcement learning-based resource allocation framework is developed to jointly optimize the channel allocation and power control to satisfy the heterogeneous Quality-of-Service (QoS…”
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Vehicle Edge Computing Task Offloading Strategy Based on Multi-Agent Deep Reinforcement Learning: Vehicle Edge Computing Task Offloading Strategy Based Autor Bo, Jianxiong, Zhao, Xu

“…With the rapid advancement of autonomous driving technology, the volume of data generated by vehicle sensors is growing exponentially. Due to spatial…”
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