Suchergebnisse - "multi-agent deep deterministic policy gradient algorithm"

A multi-agent deep deterministic policy gradient algorithm integrated with the A* algorithm for multiple-equipment integrated scheduling in automated container terminals

Autoren: Jun Li Hanping Xiao Zhixiong Liu

Quelle: Engineering Optimization. :1-24

Simulation optimization of highway hard shoulder running based on multi-agent deep deterministic policy gradient algorithm

Autoren: Lipeng Hu Jinjun Tang Guoqing Zou et al.

Quelle: Alexandria Engineering Journal, Vol 117, Iss, Pp 99-115 (2025)

Schlagwörter: MADDPG, SUMO, Spatial-temporal constrains, Highway, TA1-2040, Hard Shoulder Running, Engineering (General). Civil engineering (General)

Zugangs-URL: https://doaj.org/article/1e503378295644f3a614e59f62485d87

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

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

Quelle: Research outputs 2022 to 2026

Index Begriffe: deep deterministic policy gradient, dual active bridge converter, fractional-order concept, Hardware-in-Loop, multi-agent, reinforcement learning technique, Electrical and Computer Engineering, Engineering, text

URL: https://ro.ecu.edu.au/ecuworks2022-2026/6501

Bidding Strategy for Thermal Power Generation Companies Based on Multi-agent Deep Deterministic Policy Gradient Algorithm

Autoren: Xingping ZHANG Teng WANG Xinyue ZHANG et al.

Quelle: Zhongguo dianli, Vol 57, Iss 11, Pp 161-172 (2024)

Schlagwörter: QC501-721, TK1001-1841, Production of electric energy or power. Powerplants. Central stations, Electricity, multi-agent, bidding strategy, thermal power generation companies, new energy penetration, clearing mechanism

Zugangs-URL: https://doaj.org/article/dda079690fa440599c01a92a2ea2ec4b

Multiple unmanned aerial vehicle coordinated strikes against ground targets based on an improved multi-agent deep deterministic policy gradient algorithm

Autoren: Wei Li Xin Chen Wei Yu et al.

Quelle: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering.

Schlagwörter: 0203 mechanical engineering, 0103 physical sciences, 02 engineering and technology, 01 natural sciences

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

Autoren: Seyyed Morteza Ghamari Daryoush Habibi Asma Aziz

Quelle: Energies, Vol 18, Iss 12, p 3046 (2025)

Schlagwörter: reinforcement learning technique, Technology, fractional-order concept, deep deterministic policy gradient, multi-agent, dual active bridge converter, Hardware-in-Loop

Zugangs-URL: https://doaj.org/article/4d16de7de27346aa8f77b5ab4879ecc3

Optimal operation of regional integrated energy system based on multi-agent deep deterministic policy gradient algorithm

Autoren: Bohan Xu Yue Xiang

Quelle: Energy Reports, Vol 8, Iss, Pp 932-939 (2022)

Schlagwörter: Deep deterministic policy gradient algorithm, Multi-agent scheduling, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, Integrated energy system, 7. Clean energy, TK1-9971

Zugangs-URL: https://doaj.org/article/0cba414a36bd47729997298702948607

A Pursuit Strategy for Multi-Agent Pursuit-Evasion Game via Multi-Agent Deep Deterministic Policy Gradient Algorithm

Autoren: Jianfeng Ye Qing Wang Bei Ma et al.

Quelle: 2022 IEEE International Conference on Unmanned Systems (ICUS). :418-423

Schlagwörter: 0209 industrial biotechnology, 02 engineering and technology

Multi-Agent Deep Deterministic Policy Gradient Algorithm Based on Classification Experience Replay

Autoren: Xiaoying Sun Jinchao Chen Chenglie Du et al.

Quelle: 2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ). :988-992

Schlagwörter: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Multi-Microgrid Energy Trading Strategy Based on Multi-Agent Deep Deterministic Policy Gradient Algorithm

Autoren: Genhong Qi Lingxiao Fu Meng Wang et al.

Quelle: Applied Mathematics and Nonlinear Sciences. 9

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

Autoren: Qiong Huang Ying Si Haoyu Wang

Quelle: International Journal of Advanced Computer Science and Applications. 15

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

Autoren: Junsong Lu Zongsheng Wang Kang Pan et al.

Quelle: Journal of Physics: Conference Series. 2858:012037

Simulation optimization of highway hard shoulder running based on multi-agent deep deterministic policy gradient algorithm.

Autoren: Hu, Lipeng Tang, Jinjun Zou, Guoqing et al.

Quelle: Alexandria Engineering Journal. Apr2025, Vol. 117, p99-115. 17p.

Schlagwörter: Travel time (Traffic engineering), Carbon emissions, Traffic congestion, Reinforcement learning, Environmental protection, Intelligent transportation systems

MADDPG: Multi-agent Deep Deterministic Policy Gradient Algorithm for Formation Elliptical Encirclement and Collision Avoidance

Autoren: Leixin Xu Weibin Chen Xiang Liu et al.

Quelle: Lecture Notes in Electrical Engineering ISBN: 9789811939976

Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraints

Autoren: Samende, Cephas Cao, Jun Fan, Zhong

Index Begriffe: Electrical Engineering and Systems Science - Systems and Control, text

URL: http://arxiv.org/abs/2108.09053

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)

Autoren: 窦 迅 邓叶航 王顺江 et al.

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

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

Multi-agent deep deterministic policy gradient algorithm for peer-to-peer energy trading considering distribution network constraints

Autoren: Samende, C Cao, J Fan, Z

Quelle: Applied Energy. 317:119123

Schlagwörter: T1, FOS: Electrical engineering, electronic engineering, information engineering, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Systems and Control (eess.SY), 02 engineering and technology, Q1, QA, Electrical Engineering and Systems Science - Systems and Control, 7. Clean energy

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/abs/2108.09053
https://eprints.keele.ac.uk/10735/1/2108.09053v1.pdf
https://eprints.keele.ac.uk/10980/7/1-s2.0-S0306261922005025-main.pdf

基于多智能体深度确定策略梯度算法的 火力发电商竞价策略. (Chinese)

Alternate Title: Bidding Strategy for Thermal Power Generation Companies Based on Multi-agent Deep Deterministic Policy Gradient Algorithm. (English)

Autoren: 张兴平 王腾 张馨月 et al.

Quelle: Electric Power; Nov2024, Vol. 57 Issue 11, p161-172, 12p

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

Autoren: Changdong YU Xinyang LIU Cong CHEN et al.

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

Schlagwörter: 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

Dateibeschreibung: electronic resource

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

Zugangs-URL: https://doaj.org/article/018c9e6c89c14515a342b69917ebb237

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

Autoren: Lu, Junsong Wang, Zongsheng Pan, Kang et al.

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