Suchergebnisse - Distributed neural policy gradient algorithm~

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

Autoren: Pengcheng Dai Yuanqiu Mo Wenwu Yu et al.

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

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

Zugangs-URL: http://arxiv.org/abs/2505.24113

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

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

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

Schlagwörter: 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

Autoren: Matoses Gimenez, Andreu

Index Begriffe: 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

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

Autoren: Guo, Zhen‐yu Li, Zhong‐qi

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

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

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

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

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

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

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

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

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

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

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

Autoren: YINBIN HAN RAZAVIYAYN, MEISAM RENYUAN XU

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

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

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

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

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

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

Distributed neural network-based policy gradient reinforcement learning for multi-robot formations

Autoren: Wen Shang Dong Sun

Quelle: 2008 International Conference on Information and Automation. :113-118

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

Zugangs-URL: https://ieeexplore.ieee.org/document/4607978/
http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000004607978
http://ieeexplore.ieee.org/document/4607978/

A Three-Stage Optimal Operation Strategy of Interconnected Microgrids With Rule-Based Deep Deterministic Policy Gradient Algorithm

Autoren: Huifeng Zhang Dong Yue Chunxia Dou et al.

Quelle: IEEE Transactions on Neural Networks and Learning Systems. 35:1773-1784

Schlagwörter: Optimization, Load modeling, Stakeholders, Privacy, Privacy information, Energy management, Computational modeling, Microgrids, Potential game, Optimal operation, Power generation

Dateibeschreibung: application/pdf

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/35771789

A Policy Gradient Algorithm to Alleviate the Multi-Agent Value Overestimation Problem in Complex Environments.

Autoren: Yang, Yang Li, Jiang Hou, Jinyong et al.

Quelle: Sensors (14248220); Dec2023, Vol. 23 Issue 23, p9520, 25p

Schlagwörter: REINFORCEMENT learning, MACHINE learning, GROUP decision making, ALGORITHMS, SUPPLY & demand, DISTRIBUTED algorithms

Energy saving strategy of cloud data computing based on convolutional neural network and policy gradient algorithm.

Autoren: Yang, Dexian Yu, Jiong Du, Xusheng et al.

Quelle: PLoS ONE; 12/30/2022, Vol. 17 Issue 12, p1-18, 18p

Schlagwörter: CONVOLUTIONAL neural networks, REINFORCEMENT learning, CLOUD computing, ARTIFICIAL neural networks, VIRTUAL machine systems

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

Autoren: Kulkarni, Prerita Doohan, Nitika Vats

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

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

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

Autoren: Ma, Zhu Chen, Yonglin Pan, Tianhong

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

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

A multiagent deep deterministic policy gradient-based distributed protection method for distribution network.

Autoren: Zeng, Peng Cui, Shijie Song, Chunhe et al.

Quelle: Neural Computing & Applications. Jan2023, Vol. 35 Issue 3, p2267-2278. 12p.

Schlagwörter: *DISTRIBUTED power generation, *BURGLARY protection

Comparison of machine learning algorithms and multiple linear regression for live weight estimation of Akkaraman lambs.

Autoren: Kozaklı, Özge Ceyhan, Ayhan Noyan, Mevlüt

Quelle: Tropical Animal Health & Production. Sep2024, Vol. 56 Issue 7, p1-10. 10p.

Efficient off‐policy Q‐learning for multi‐agent systems by solving dual games.

Autoren: Wang, Yan Xue, Huiwen Wen, Jiwei et al.

Quelle: International Journal of Robust & Nonlinear Control. Apr2024, Vol. 34 Issue 6, p4193-4212. 20p.

Schlagwörter: *MULTIAGENT systems, *ZERO sum games, *TRACKING algorithms, *MULTIPLAYER games, *DISTRIBUTED algorithms, *NASH equilibrium

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

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

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

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

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

Schlagwörter: *DEEP reinforcement learning, *NOISE control, *DEBUGGING, *NOISE, *ALGORITHMS, *REINFORCEMENT learning

Adaptive partitioning and efficient scheduling for distributed DNN training in heterogeneous IoT environment.

Autoren: Huang, Binbin Huang, Xunqing Liu, Xiao et al.

Quelle: Computer Communications. Feb2024, Vol. 215, p169-179. 11p.

Schlagwörter: *DYNAMIC programming, *SCHEDULING, INTERNET of things, PARTICLE swarm optimization, GENETIC algorithms, DISTRIBUTED algorithms