Výsledky vyhľadávania - Distributed multi-agent deep deterministic policy gradient algorithm~

Distributed Deep Deterministic Policy Gradient for Power Allocation Control in D2D-Based V2V Communications

Autori: Khoi Khac Nguyen Trung Q. Duong Ngo Anh Vien a ďalší

Zdroj: IEEE Access, Vol 7, Pp 164533-164543 (2019)
Nguyen, K K, Duong, T Q, Vien, N A, Le-Khac, N-A & Nguyen, L D 2019, 'Distributed Deep Deterministic Policy Gradient for Power Allocation Control in D2D-Based V2V Communications', IEEE Access, vol. 7, pp. 164533-164543. https://doi.org/10.1109/ACCESS.2019.2952411

Predmety: Artificial intelligence, Device-to-Device Communication, Flexibility (engineering), Wireless Energy Harvesting and Information Transfer, name=SDG 7 - Affordable and Clean Energy, 02 engineering and technology, name=General Materials Science, name=General Computer Science, Engineering, Quality of service, Reinforcement learning, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, name=General Engineering, Electrical and Electronic Engineering, Resource allocation, Computer network, multi-agent deep reinforcement learning, Non-cooperative D2D communication, Statistics, Next Generation 5G Wireless Networks, power allocation, Intelligent Reflecting Surfaces in Wireless Communications, Computer science, and deep deterministic policy gradient (DDPG), Distributed computing, name=SDG 11 - Sustainable Cities and Communities, TK1-9971, D2D-based V2V communications, Physical Sciences, Electrical engineering. Electronics. Nuclear engineering, Mathematics

Popis súboru: application/pdf

Prístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08894348.pdf
https://doaj.org/article/df3daab963154d1aa51d6faf43d94dc9
https://pure.qub.ac.uk/en/publications/distributed-deep-deterministic-policy-gradient-for-power-allocati
https://ieeexplore.ieee.org/document/8894348
https://dblp.uni-trier.de/db/journals/access/access7.html#NguyenDVLN19a
https://pureadmin.qub.ac.uk/ws/files/195379913/08894348.pdf
https://pure.qub.ac.uk/en/publications/e594ac54-7e6e-41a5-a3f5-642efe013cf2

Distributed auto disturbances rejection resilient control of permanent magnetic maglev trains based on the optimized deep deterministic policy gradient algorithm.

Autori: Guo, Zhen‐yu Li, Zhong‐qi

Zdroj: IET Control Theory & Applications (Wiley-Blackwell). Jul2024, Vol. 18 Issue 11, p1383-1397. 15p.

Predmety: *MAGNETIC levitation vehicles, *MAGNETIC control, *PARTICLE swarm optimization, *ALGORITHMS, *UNCERTAIN systems

基于改进多智能体深度确定策略梯度算法的 配电网无功协调优化调度: 79 95 23. (Chinese)

Alternate Title: Reactive power coordination optimization scheduling of distribution network based on improved multi-agent deep deterministic policy gradient algorithm. (English)

Autori: 窦 迅 邓叶航 王顺江 a ďalší

Zdroj: Electric Power Automation Equipment / Dianli Zidonghua Shebei; Aug2025, Vol. 45 Issue 8, p79-95, 23p

Predmety: PARTICLE swarm optimization, ELECTRICAL load, REINFORCEMENT learning, DEEP reinforcement learning, REWARD (Psychology)

Robust Adaptive Fractional-Order PID Controller Design for High-Power DC-DC Dual Active Bridge Converter Enhanced Using Multi-Agent Deep Deterministic Policy Gradient Algorithm for Electric Vehicles.

Autori: Ghamari, Seyyed Morteza Habibi, Daryoush Aziz, Asma

Zdroj: Energies (19961073); Jun2025, Vol. 18 Issue 12, p3046, 34p

Predmety: PID controllers, REINFORCEMENT learning, VOLTAGE control, POLITICAL succession, ELECTRIC vehicles

Distributed Drive Autonomous Vehicle Trajectory Tracking Control Based on Multi-Agent Deep Reinforcement Learning

Autori: Yalei Liu Weiping Ding Mingliang Yang a ďalší

Zdroj: Mathematics, Vol 12, Iss 11, p 1614 (2024)

Predmety: distributed drive autonomous vehicles, trajectory tracking, multi-agent deep reinforcement learning, deep deterministic policy gradient, deep Q-network, Mathematics, QA1-939

Popis súboru: electronic resource

Relation: https://www.mdpi.com/2227-7390/12/11/1614; https://doaj.org/toc/2227-7390

Prístupová URL adresa: https://doaj.org/article/0f3b3713594d428b95971d71141486c5

Research on Game Confrontation of Unmanned Surface Vehicles Swarm Based on Multi-Agent Deep Reinforcement Learning

Autori: Changdong YU Xinyang LIU Cong CHEN a ďalší

Zdroj: 水下无人系统学报, Vol 32, Iss 1, Pp 79-86 (2024)

Predmety: unmanned surface vehicle swarm, multi-agent deep deterministic policy gradient algorithm, deep reinforcement learning, intelligent decision-making, game confrontation, Naval architecture. Shipbuilding. Marine engineering, VM1-989

Popis súboru: electronic resource

Relation: https://doaj.org/toc/2096-3920

Prístupová URL adresa: https://doaj.org/article/018c9e6c89c14515a342b69917ebb237

An intelligent MIMO run-to-run controller for semiconductor manufacturing processes based on an enhanced twin-delayed deep deterministic policy gradient algorithm.

Autori: Ma, Zhu Chen, Yonglin Pan, Tianhong

Zdroj: Applied Intelligence; Jul2025, Vol. 55 Issue 10, p1-25, 25p

Predmety: DEEP reinforcement learning, REINFORCEMENT learning, ARTIFICIAL intelligence, MANUFACTURING processes, INTELLIGENT control systems, SEMICONDUCTOR manufacturing

Adaptive Load Balancing In Sdns Using A Fuzzy-Driven Twin Delayed Deep Deterministic Policy Gradient Algorithm.

Autori: Kulkarni, Prerita Doohan, Nitika Vats

Zdroj: International Journal of Environmental Sciences (2229-7359); 2025 Special Issue, Vol. 11, p2171-2181, 11p

Predmety: LOAD balancing (Computer networks), SOFTWARE-defined networking, REINFORCEMENT learning, FUZZY logic, RESOURCE allocation

Optimal bidding strategy for the price-maker virtual power plant in the day-ahead market based on multi-agent twin delayed deep deterministic policy gradient algorithm.

Autori: Jiang, Yuzheng Dong, Jun Huang, Hexiang

Zdroj: Energy. Oct2024, Vol. 306, pN.PAG-N.PAG. 1p.

Predmety: *OPTIMIZATION algorithms, *BIDDING strategies, *REINFORCEMENT learning, *ELECTRICITY markets, *ELECTRICITY pricing

Deep Reinforcement Learning for Ecological and Distributed Urban Traffic Signal Control with Multi-Agent Equilibrium Decision Making.

Autori: Yan, Liping Wang, Jing

Zdroj: Electronics (2079-9292); May2024, Vol. 13 Issue 10, p1910, 21p

Predmety: DEEP reinforcement learning, TRAFFIC signs & signals, TRAFFIC engineering, CITY traffic, THERMODYNAMIC control, REINFORCEMENT learning, DISTRIBUTED algorithms

Fire Evacuation Path Planning Based on Improved MADDPG (Multi-Agent Deep Deterministic Policy Gradient) Algorithm.

Autori: Qiong Huang Ying Si Haoyu Wang

Zdroj: International Journal of Advanced Computer Science & Applications; Jul2024, Vol. 15 Issue 7, p387-395, 9p

Research on the influence of multi-agent deep deterministic policy gradient algorithm key parameters in typical scenarios.

Autori: Lu, Junsong Wang, Zongsheng Pan, Kang a ďalší

Zdroj: Journal of Physics: Conference Series; 2024, Vol. 2858 Issue 1, p1-12, 12p

Optimal demand response based dynamic pricing strategy via Multi-Agent Federated Twin Delayed Deep Deterministic policy gradient algorithm.

Autori: Ma, Haining Zhang, Huifeng Tian, Ding a ďalší

Zdroj: Engineering Applications of Artificial Intelligence. Jul2024:Part A, Vol. 133, pN.PAG-N.PAG. 1p.

Predmety: *TIME-based pricing, *FEDERATED learning, *REINFORCEMENT learning, *LOAD management (Electric power), *DISTRIBUTED algorithms, *ALGORITHMS

A Hierarchical Reinforcement Learning Framework for Multi-Agent Cooperative Maneuver Interception in Dynamic Environments.

Autori: Huang, Qinlong Luo, Yasong Liu, Zhong a ďalší

Zdroj: Journal of Marine Science & Engineering; Jul2025, Vol. 13 Issue 7, p1271, 32p

Predmety: REINFORCEMENT learning, GRAPH neural networks, MULTIAGENT systems, RESOURCE management, DEEP learning, ROBOTIC path planning

Adaptive Deep Ant Colony Optimization–Asymmetric Strategy Network Twin Delayed Deep Deterministic Policy Gradient Algorithm: Path Planning for Mobile Robots in Dynamic Environments.

Autori: Li, Xiangcheng Ruan, Zhaokai Ou, Yang a ďalší

Zdroj: Electronics (2079-9292); Oct2024, Vol. 13 Issue 20, p4071, 22p

Predmety: ANT algorithms, ROBOTIC path planning, MACHINE learning, DEEP learning, MOBILE learning, MOBILE robots

Friend-or-Foe Deep Deterministic Policy Gradient

Autori: Dianxi Shi Gongju Wang Chao Xue a ďalší

Zdroj: 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). :3523-3530

Predmety: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences

Prístupová URL adresa: https://dblp.uni-trier.de/db/conf/smc/smc2020.html#JiangSXWWZ20a

Twin-Delayed Deep Deterministic Policy Gradient Algorithm to Control a Boost Converter in a DC Microgrid.

Autori: Muktiadji, Rifqi Firmansyah Ramli, Makbul A. M. Milyani, Ahmad H.

Zdroj: Electronics (2079-9292); Jan2024, Vol. 13 Issue 2, p433, 22p

Predmety: MICROGRIDS, BOOSTING algorithms, REINFORCEMENT learning, DEEP learning, ENGINEERING design, VOLTAGE control, REACTION time

Large-scale multi-agent reinforcement learning-based method for coordinated output voltage control of solid oxide fuel cell

Autori: Jiawen Li Yaping Li Tao Yu a ďalší

Zdroj: Case Studies in Thermal Engineering, Vol 30, Iss , Pp 101752- (2022)

Predmety: Large-scale deep reinforcement learning, Pygmalion effect-based multi-agent double delay deep deterministic policy gradient algorithm (PEB-MA4DPG), DC/DC converter, Fuel reformer, Output voltage coordinated control, Solid oxide fuel cell (SOFC), Engineering (General). Civil engineering (General), TA1-2040

Popis súboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2214157X21009151; https://doaj.org/toc/2214-157X

Prístupová URL adresa: https://doaj.org/article/c6b60fb0b22c481ca8065bede3ebb574

Distributed Drive Autonomous Vehicle Trajectory Tracking Control Based on Multi-Agent Deep Reinforcement Learning.

Autori: Liu, Yalei Ding, Weiping Yang, Mingliang a ďalší

Zdroj: Mathematics (2227-7390); Jun2024, Vol. 12 Issue 11, p1614, 21p

Predmety: DEEP reinforcement learning, REINFORCEMENT learning, AUTONOMOUS vehicles, MOTOR vehicle driving, TORQUE control, MARKOV processes

Orbital Multi-Player Pursuit-Evasion Game with Deep Reinforcement Learning.

Autori: Li, Zhen-yu Chen, Si Zhou, Chenghong a ďalší

Zdroj: Journal of the Astronautical Sciences; Feb2025, Vol. 72 Issue 1, p1-29, 29p

Predmety: REINFORCEMENT learning, DEEP reinforcement learning, MULTIPLAYER games, MACHINE learning, ALGORITHMS