Search Results - Distributed neural policy gradient algorithm*

Distributed Neural Policy Gradient Algorithm for Global Convergence of Networked Multi-Agent Reinforcement Learning

Authors: Pengcheng Dai Yuanqiu Mo Wenwu Yu et al.

Source: IEEE Transactions on Automatic Control. :1-16

Subject Terms: FOS: Computer and information sciences, Computer Science - Multiagent Systems, Multiagent Systems (cs.MA)

Access URL: http://arxiv.org/abs/2505.24113

Distributed Policy Gradient with Variance Reduction in Multi-Agent Reinforcement Learning.

Authors: Zhao, Xiaoxiao Lei, Jinlong Li, Li et al.

Source: Journal of Systems Science & Complexity; Oct2025, Vol. 38 Issue 5, p1853-1886, 34p

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)

Application of AI Optimization Algorithms to Service-Oriented Architecture Design.

Authors: Xie, Fei

Source: Journal of Combinatorial Mathematics & Combinatorial Computing; Dec2025, Vol. 127a, p5851-5869, 19p

Subject Terms: SERVICE-oriented architecture (Computer science), DISTRIBUTED computing, INFORMATION storage & retrieval systems, REINFORCEMENT learning, CLOUD computing, QUALITY of service

A New Proposal for Intelligent Continuous Controller of Robotic Finger Prostheses Using Deep Deterministic Policy Gradient Algorithm Through Simulated Assessments.

Authors: Rúbio, Guilherme de Paula Costa, Matheus Carvalho Barbosa Vimieiro, Claysson Bruno Santos

Source: Robotics; Apr2025, Vol. 14 Issue 4, p49, 24p

Subject Terms: ARTIFICIAL neural networks, MYOELECTRIC prosthesis, REINFORCEMENT learning, ARTIFICIAL hands, INTELLIGENT control systems

Scalable Reinforcement Learning for Formation Control with Collision Avoidance : Localized policy gradient algorithm with continuous state and action space

Additional Titles: Skalbar Förstärkande Inlärning för Formationskontroll med Kollisionsundvikande : Lokaliserad policygradientalgoritm med kontinuerligt tillstånds och handlingsutrymme

Authors: Matoses Gimenez, Andreu

Index Terms: Control theory, Multi-agent systems, Distributed systems, Formation control, Collision avoidance, Reinforcement learning, Teoria de control, Sistemes multiagent, Sistemes distribuïts, Control de formació, Prevenció de col·lisions, Reinforcement Learning, Reglerteknik, Multi-agent system, Distribuerade system, formationskontroll, Kollisionsundvikande, Teoría de control, Sistemas multiagente, Sistemas distribuidos, Control de formación, Prevención de colisiones, Computer graphics and computer vision, Datorgrafik och datorseende, Control Engineering, Electrical Engineering, Electronic Engineering, Information Engineering, Elektroteknik och elektronik, Student thesis, info:eu-repo/semantics/bachelorThesis, text

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-325793
TRITA-EECS-EX ; 2023:85

Lightweight deep deterministic policy gradient for edge computing in recirculating aquaculture systems: real-time feeding control with reduced computational requirements.

Authors: Elmessery, Wael M. Shams, Mahmoud Y. El-Hafeez, Tarek Abd et al.

Source: Scientific Reports; 10/30/2025, Vol. 15 Issue 1, p1-24, 24p

Subject Terms: EDGE computing, AQUACULTURE, REINFORCEMENT learning, SUSTAINABLE aquaculture, ARTIFICIAL neural networks, RESOURCE management

Real-time dynamic path planning for distributed unmanned surface vehicles in coordinated formations with maneuverability constraints.

Authors: Chen, Xizhe Yin, Shihong Li, Yujing et al.

Source: Applied Intelligence; Jul2025, Vol. 55 Issue 10, p1-17, 17p

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

Authors: Guo, Zhen‐yu Li, Zhong‐qi

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

Subject Terms: MAGNETIC levitation vehicles, MAGNETIC control, PARTICLE swarm optimization, ALGORITHMS, UNCERTAIN systems

A manipulator control method based on deep deterministic policy gradient with parameter noise.

Authors: Zhang, Haifei Xu, Jian Lei, Liting et al.

Source: Neural Computing & Applications; Feb2025, Vol. 37 Issue 4, p1729-1739, 11p

Subject Terms: DEEP reinforcement learning, NOISE control, DEBUGGING, NOISE, ALGORITHMS, REINFORCEMENT learning

A distributed adaptive policy gradient method based on momentum for multi-agent reinforcement learning.

Authors: Shi, Junru Wang, Xin Zhang, Mingchuan et al.

Source: Complex & Intelligent Systems; Oct2024, Vol. 10 Issue 5, p7297-7310, 14p

Subject Terms: REINFORCEMENT learning, MACHINE learning, SAMPLING (Process), CHANGE agents, ALGORITHMS

Dual experience replay enhanced deep deterministic policy gradient for efficient continuous data sampling.

Authors: Mohd Aris, Teh Noranis Chen, Ningning Mustapha, Norwati et al.

Source: PLoS ONE; 11/11/2025, Vol. 20 Issue 11, p1-18, 18p

Subject Terms: REINFORCEMENT learning, SAMPLING (Process), SAMPLING methods

A Reinforcement Learning-Based Approach for Distributed Photovoltaic Carrying Capacity Analysis in Distribution Grids.

Authors: Sun, Shumin Yang, Song Yu, Peng et al.

Source: Energies (19961073); Sep2025, Vol. 18 Issue 18, p5029, 19p

Subject Terms: REINFORCEMENT learning, PHOTOVOLTAIC power systems, COMPUTER simulation, OPTIMIZATION algorithms, ELECTRIC power distribution grids, EVALUATION methodology

Data-Based Optimal Consensus Control for Multiagent Systems With Policy Gradient Reinforcement Learning.

Authors: Yang, Xindi Zhang, Hao Wang, Zhuping

Source: IEEE Transactions on Neural Networks & Learning Systems; Aug2022, Vol. 33 Issue 8, p3872-3883, 12p

Subject Terms: MULTIAGENT systems, REINFORCEMENT learning, DISTRIBUTED algorithms, ASYNCHRONOUS learning, MACHINE learning, DISCRETE-time systems, APPROXIMATION error

Exploring reinforcement learning in process control: a comprehensive survey.

Authors: Rajasekhar, N. Radhakrishnan, T.K. Samsudeen, N.

Source: International Journal of Systems Science; Oct2025, Vol. 56 Issue 14, p3528-3557, 30p

Subject Terms: REINFORCEMENT learning, PROCESS control systems, MACHINE learning, DECISION making, ALGORITHMS, DEEP learning, INDUSTRIAL applications

Autonomous Vehicle Trajectory Tracking Control Based on Deep Deterministic Policy Gradient Algorithm and Crayfish Optimization Algorithm.

Authors: Wang, Le Lu, Hongrui Su, Qingyang et al.

Source: Symmetry (20738994); Sep2025, Vol. 17 Issue 9, p1396, 29p

Subject Terms: AUTONOMOUS vehicles, OPTIMIZATION algorithms, TRAJECTORY measurements, REINFORCEMENT learning, MATHEMATICAL optimization

POLICY GRADIENT CONVERGES TO THE GLOBALLY OPTIMAL POLICY FOR NEARLY LINEAR-QUADRATIC REGULATORS.

Authors: YINBIN HAN RAZAVIYAYN, MEISAM RENYUAN XU

Source: SIAM Journal on Control & Optimization; 2025, Vol. 63 Issue 4, p2936-2963, 28p

Subject Terms: REINFORCEMENT learning, OPTIMIZATION algorithms, NONLINEAR control theory, DYNAMICAL systems, FEEDBACK control systems, COST functions

FAMASO: fog-adaptive multi-agent scheduling optimization.

Authors: Nagabushnam, Ganesan Kim, Kyong Hoon Choi, Yundo

Source: Cluster Computing; 2025, Vol. 28 Issue 8, p1-38, 38p

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

Authors: Huang, Qinlong Luo, Yasong Liu, Zhong et al.

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

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

Collaborative task decision-making of multi-UUV in dynamic environments based on deep reinforcement learning.

Authors: Yu, Haomiao Zhang, Sijie

Source: Ships & Offshore Structures; Oct2025, Vol. 20 Issue 9, p1272-1282, 11p

Subject Terms: REINFORCEMENT learning, MARKOV processes, AUTONOMOUS robots, ROBOTIC path planning, REMOTE submersibles, ALGORITHMS, DYNAMICAL systems