Search Results - Distributed multi-agent deep deterministic policy gradient algorithm

Distributed Deep Deterministic Policy Gradient for Power Allocation Control in D2D-Based V2V Communications by 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…”
Get full text

A multi-agent deep reinforcement learning-based “Octopus” cooperative load frequency control for an interconnected grid with various renewable units by 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…”
Get full text

A Dynamic Deceptive Defense Framework for Zero-Day Attacks in IIoT: Integrating Stackelberg Game and Multi-Agent Distributed Deep Deterministic Policy Gradient by 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…”
Get full text

Multi-Agent DRL for Air-to-Ground Communication Planning in UAV-Enabled IoT Networks by 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…”
Get full text

Multi-Agent Reinforcement Learning using the Deep Distributed Distributional Deterministic Policy Gradients Algorithm by Farag, Wael

“…In this paper, the Deep Distributed Distributional Deterministic Policy Gradients (D4PG…”
Get full text

3DPG: Distributed Deep Deterministic Policy Gradient Algorithms for Networked Multi-Agent Systems by Redder, Adrian, Ramaswamy, Arunselvan, Karl, Holger

“…We present Distributed Deep Deterministic Policy Gradient (3DPG), a multi-agent actor-critic (MAAC…”
Get full text

Optimal demand response based dynamic pricing strategy via Multi-Agent Federated Twin Delayed Deep Deterministic policy gradient algorithm by 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…”
Get full text

Friend-or-Foe Deep Deterministic Policy Gradient by 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…”
Get full text

Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learning by 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…”
Get full text

Distributed MA‐IDDPG‐OLSR based stable routing protocol for unmanned aerial vehicle ad‐hoc network by 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…”
Get full text

Multi-Agent DDPG-Based Multi-Device Charging Scheduling for IIoT Smart Grids by 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…”
Get full text

Multi-agent learning based UAV-assisted MEC-NOMA for cellular offloading in Internet of Things by 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…”
Get full text

Joint Multi-objective Optimization for Radio Access Network Slicing Using Multi-agent Deep Reinforcement Learning by 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…”
Get full text

Optimal Bi-Level Bidding and Dispatching Strategy Between Active Distribution Network and Virtual Alliances Using Distributed Robust Multi-Agent Deep Reinforcement Learning by 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…”
Get full text

Multi-agent distributed deep reinforcement learning algorithm in cloud environment by 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…”
Get full text

Vehicle Edge Computing Task Offloading Strategy Based on Multi-Agent Deep Reinforcement Learning by 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…”
Get full text

Post-Disaster Generation Dispatching for Enhanced Resilience: A Multi-Agent Deep Deterministic Policy Gradient Learning Approach by 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…”
Get full text

Research on Game Confrontation of Unmanned Surface Vehicles Swarm Based on Multi-Agent Deep Reinforcement Learning by 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…”
Get full text

Multiagent Deep-Reinforcement-Learning-Based Resource Allocation for Heterogeneous QoS Guarantees for Vehicular Networks by 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…”
Get full text

Vehicle Edge Computing Task Offloading Strategy Based on Multi-Agent Deep Reinforcement Learning: Vehicle Edge Computing Task Offloading Strategy Based by 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…”
Get full text