Search Results - improved multi-agent deep deterministic policy gradient algorithm*

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

Authors: Wei Li Xin Chen Wei Yu et al.

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

Subject Terms: 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

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

Source: Research outputs 2022 to 2026

Index Terms: 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

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

Authors: Qiong Huang Ying Si Haoyu Wang

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

ERA-MADDPG: An Elastic Routing Algorithm Based on Multi-Agent Deep Deterministic Policy Gradient in SDN.

Authors: Huang, Wanwei Liu, Hongchang Li, Yingying et al.

Source: Future Internet. Jul2025, Vol. 17 Issue 7, p291. 20p.

Subject Terms: Software-defined networking, Reinforcement learning, Convolutional neural networks, Adaptive control systems, Routing algorithms, Adaptive routing (Computer network management)

Improved Multi-Agent Deep Deterministic Policy Gradient for Path Planning-Based Crowd Simulation

Authors: Shangfei Zheng Hong Liu

Source: IEEE Access, Vol 7, Pp 147755-147770 (2019)

Subject Terms: Deep reinforcement learning, improved multi-agent deep deterministic policy gradient algorithm, multi-agent reinforcement learning, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, crowd simulation for evacuation, path planning, TK1-9971

Access URL: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08865095.pdf
https://doaj.org/article/f1c103a658d8479f943e594a29828bd1
https://dblp.uni-trier.de/db/journals/access/access7.html#ZhengL19
https://ieeexplore.ieee.org/abstract/document/8865095

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

Authors: Seyyed Morteza Ghamari Daryoush Habibi Asma Aziz

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

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

Access URL: https://doaj.org/article/4d16de7de27346aa8f77b5ab4879ecc3

A Hybrid Optimization Algorithm for Efficient Virtual Machine Migration and Task Scheduling Using a Cloud-Based Adaptive Multi-Agent Deep Deterministic Policy Gradient Technique

Authors: Et al. Gurpreet Singh Panesar

Source: International Journal on Recent and Innovation Trends in Computing and Communication. 11:742-756

Subject Terms: 12. Responsible consumption

ERA-MADDPG: An Elastic Routing Algorithm Based on Multi-Agent Deep Deterministic Policy Gradient in SDN

Authors: Wanwei Huang Hongchang Liu Yingying Li et al.

Source: Future Internet, Vol 17, Iss 7, p 291 (2025)

Subject Terms: SDN, DDPG, routing algorithm, multi-agent, actor-critic, Information technology, T58.5-58.64, network topology

Access URL: https://doaj.org/article/85792b9f010547ff88e679971526d564

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)

Authors: 窦 迅 邓叶航 王顺江 et al.

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

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

A Hybrid Optimization Algorithm for Efficient Virtual Machine Migration and Task Scheduling Using a Cloud-Based Adaptive Multi-Agent Deep Deterministic Policy Gradient Technique

Authors: Panesar , Gurpreet Singh Chadha, Raman

Source: International Journal of Intelligent Systems and Applications in Engineering; Vol. 12 No. 6s (2024); 30-45

Subject Terms: Iterative Concept of War and Rat Swarm (ICWRS), War Strategy Optimization (WSO), Deep Deterministic Policy Gradient (DDPG), System Optimization, Adaptive Multi-Agent System (AMS), Rat Swarm Optimizer (RSO), 12. Responsible consumption

File Description: application/pdf

Access URL: https://www.ijisae.org/index.php/IJISAE/article/view/3928

A Q-Learning-based Deep Deterministic Policy Gradient Algorithm for the Re-entrant Hybrid Flow Shop Joint Scheduling Problem with Dual-gripper.

Authors: Jiajia Wang Hongming Zhou Jian Guo et al.

Source: Engineering Letters. May2025, Vol. 33 Issue 5, p1632-1647. 16p.

Subject Terms: *FLOW shop scheduling, *FLOW shops, *MULTIAGENT systems, *PRODUCTION scheduling, *MATHEMATICAL models, *MANUFACTURING workstations

Multi-objective optimal scheduling strategy of energy storage system based on improved multi-agent deep deterministic policy gradient.

Authors: Wang, Yufei Gu, Ruixin Wang, Yishun et al.

Source: Electric Power Systems Research. Oct2025, Vol. 247, pN.PAG-N.PAG. 1p.

Subject Terms: *DEEP reinforcement learning, *REINFORCEMENT learning, *ENERGY storage, *MULTI-objective optimization, *POWER resources

RS-MADDPG: Routing Strategy Based on Multi-Agent Deep Deterministic Policy Gradient for Differentiated QoS Services.

Authors: Kuang, Shi Zheng, Jinyu Liang, Shilin et al.

Source: Future Internet; Sep2025, Vol. 17 Issue 9, p393, 20p

Subject Terms: QUALITY of service, ADAPTIVE routing (Computer network management), ROUTING algorithms, SOFTWARE-defined networking, MULTIAGENT systems, QUANTITATIVE research, REINFORCEMENT learning

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

Authors: Shigen Shen Xiaojun Ji Yimeng Liu

Source: Computers, Materials & Continua ; ISSN: 1546-2218 (Print) ; ISSN: 1546-2226 (Online) ; Volume 85 ; Issue 2

Subject Terms: Industrial internet of things, zero-day attacks, Stackelberg game, distributed deep deterministic policy gradient, defensive spoofing, dynamic defense

File Description: application/pdf

Relation: https://doi.org/10.32604/cmc.2025.069332

Availability: https://doi.org/10.32604/cmc.2025.069332

Novel multiagent reinforcement learning framework using twin delayed deep deterministic policy gradient for adaptive PID control in boiler turbine systems.

Authors: Kruthika, U. Paneerselvam, Surekha

Source: Scientific Reports; 10/3/2025, Vol. 15 Issue 1, p1-30, 30p

Subject Terms: REINFORCEMENT learning, INDUSTRIAL applications, FEEDBACK control systems, STABILITY theory, INDUSTRIAL controls manufacturing, NONLINEAR control theory, MATHEMATICAL optimization

Fractional order actor critic and fractional order deep deterministic policy gradient algorithms.

Authors: Jiang, Wuzuo Dong, Jianping Dong, Yuhan

Source: Communications on Analysis & Computation (CAC); Dec2025, Vol. 6, p1-18, 18p

Subject Terms: REINFORCEMENT learning, FRACTIONAL calculus, ROBUST control, INTEGRALS, MATHEMATICAL optimization, MACHINE learning

Design of Robust Adaptive Nonlinear Backstepping Controller Enhanced by Deep Deterministic Policy Gradient Algorithm for Efficient Power Converter Regulation.

Authors: Ghamari, Seyyed Morteza Aziz, Asma Ghahramani, Mehrdad

Source: Energies (19961073); Sep2025, Vol. 18 Issue 18, p4941, 27p

Subject Terms: ADAPTIVE control systems, REINFORCEMENT learning, GREY Wolf Optimizer algorithm, NONLINEAR systems, STABILITY (Mechanics), CONVERTERS (Electronics), HARDWARE-in-the-loop simulation

Flash-Attention-Enhanced Multi-Agent Deep Deterministic Policy Gradient for Mobile Edge Computing in Digital Twin-Powered Internet of Things.

Authors: Gao, Yuzhe Yuan, Xiaoming Wang, Songyu et al.

Source: Mathematics (2227-7390); Jul2025, Vol. 13 Issue 13, p2164, 21p

Subject Terms: EDGE computing, DIGITAL twin, MULTIAGENT systems, REINFORCEMENT learning, ATTENTION, RESOURCE allocation, INTERNET of things

Research on a Cooperative Grasping Method for Heterogeneous Objects in Unstructured Scenarios of Mine Conveyor Belts Based on an Improved MATD3

Authors: Rui Gao Mengcong Liu Jingyi Du et al.

Source: Sensors, Vol 25, Iss 22, p 6824 (2025)

Subject Terms: cooperative grasping, Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3), multi-factor reward function, prioritized experience replay (PER), sequence cooperative optimization strategy, Chemical technology, TP1-1185

File Description: electronic resource

Relation: https://www.mdpi.com/1424-8220/25/22/6824; https://doaj.org/toc/1424-8220

Access URL: https://doaj.org/article/0d96ea3db2a4457d8d1f05aadd38caf9

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

Authors: Kulkarni, Prerita Doohan, Nitika Vats

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

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