Výsledky vyhledávání - "Reinforcement learning algorithm"

Federated Deep Reinforcement Learning for ENDC Optimization

Autoři: Adrian Martin Isabel de-la-Bandera Adriano Mendo a další

Zdroj: RIUMA. Repositorio Institucional de la Universidad de Málaga
Universidad de Málaga

Témata: Optimization, Handover, Learning agent, Optimal network, Deep reinforcement learning algorithm, Network capacity, Federated learning, Heterogeneous network, Deep neural network, Small step, Deep reinforcement learning agent, Key performance indicators, Aprendizaje automático (Inteligencia artificial), Reinforcement learning algorithm, Training, Heuristic algorithms, Training phase, Training cell, Individual agency, Neighboring cells, Long term evolution, Deep reinforcement learning, 5 G NSA, Telecomunicaciones, Multi party computation, Hysteresis, Cell clusters, Rest of the cells, Reinforcement learning agent, Event B 1, Cellular networks, Deep learning, RAN Optimization, Rate of network, Throughput, 5 G Mobile communication, User equipment, Mobile edge computing

Přístupová URL adresa: https://hdl.handle.net/10630/38565

Research on the implementation and effectiveness evaluation of deep reinforcement learning algorithms for portfolio optimisation

Autoři: Gao Yunxiang Tang Bangying

Zdroj: Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-12 (2025)

Témata: Deep reinforcement learning algorithm, Portfolio optimisation, Effectiveness evaluation, A2C, PPO, Computational linguistics. Natural language processing, P98-98.5, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2731-0809

Přístupová URL adresa: https://doaj.org/article/ea0dd1c5fe3c4c01b7c171ce10c6ea3d

A hybrid MARL clustering framework for real time open pit mine truck scheduling

Autoři: Xiaolei Xiang Wei Lin Danqi Li

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-23 (2025)

Témata: Multi-agent deep reinforcement learning algorithm, QMIX, Gaussian mixture model, Open-pit mining, Truck scheduling, Medicine, Science

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2045-2322

Přístupová URL adresa: https://doaj.org/article/f7ac25e2b3aa4d10b60e96df41633cce

Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks

Autoři: K. Lakshmi Prabha Hanan Abdullah Mengash Hamed Alqahtani a další

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-19 (2025)

Témata: Wireless sensor network, Multi agent reinforcement learning algorithm, Golden jack optimization, Localization error, Prediction. error minimization, Medicine, Science

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2045-2322

Přístupová URL adresa: https://doaj.org/article/6a3a125894ab45f591589f089c9401d0

Reinforcement learning control method for greenhouse vegetable irrigation driven by dynamic clipping and negative incentive mechanism

Autoři: Ruipeng Tang Jianxun Tang Mohamad Sofian Abu Talip a další

Zdroj: Frontiers in Plant Science, Vol 16 (2025)

Témata: irrigation prediction method, greenhouse vegetable irrigation, reinforcement learning algorithm, sustainable agricultural development, greenhouse vegetable production, Plant culture, SB1-1110

Popis souboru: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fpls.2025.1632431/full; https://doaj.org/toc/1664-462X

Přístupová URL adresa: https://doaj.org/article/aea71bcb360a4622903777a8ffd22273

A cooperative jamming mode adjustment method based on Multi-Agent reinforcement learning

Autoři: Jieling Wang Yanfei Liu Chao Li a další

Zdroj: Ain Shams Engineering Journal, Vol 16, Iss 11, Pp 103672- (2025)

Témata: Netted Radar System (NRS), Non-cooperative adversarial scenario model, Multi-agent reinforcement learning algorithm, Jamming mode adjusting, Alternating training, Nonlinear problems, Engineering (General). Civil engineering (General), TA1-2040

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2090447925004137; https://doaj.org/toc/2090-4479

Přístupová URL adresa: https://doaj.org/article/028047a5479048149576d324e4caa0b5

IGSA-SAC: a novel approach for intrusion detection using improved gravitational search algorithm and soft actor-critic

Autoři: Lizhong Jin Rulong Fan Xiaoling Han a další

Zdroj: Frontiers in Computer Science, Vol 7 (2025)

Témata: Soft Actor-Critic, feature selection, gravitational search algorithm, intrusion detection, Electronic computers. Computer science, QA75.5-76.95, reinforcement learning algorithm

Přístupová URL adresa: https://doaj.org/article/22cc9452df284379afd10fc3038826b0

Adaptive Multi-Scale Bidirectional TD3 Algorithm for Layout Optimization of UAV–Base Station Coordination in Mountainous Areas

Autoři: Leyi Wang Jianbo Tan Hanbo Gong a další

Zdroj: Drones, Vol 9, Iss 11, p 805 (2025)

Témata: base station layout, deep reinforcement learning algorithm, differential evolution algorithm, UAV, Motor vehicles. Aeronautics. Astronautics, TL1-4050

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2504-446X/9/11/805; https://doaj.org/toc/2504-446X

Přístupová URL adresa: https://doaj.org/article/1cadac0407b4410a9d6f0758a9d21d44

Design of a Digital Exhibition Service System Under the Deep Belief Network Models

Autoři: Qixin Song

Zdroj: IEEE Access, Vol 12, Pp 108786-108796 (2024)

Témata: digital exhibition service system, random forest algorithm, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, reinforcement learning algorithm, Deep belief network model, decision optimization, TK1-9971

Přístupová URL adresa: https://doaj.org/article/89c29732b03b49d39a166acbd887282c

A Method for Joint Edge Server Deployment and Service Placement

Autoři: ZHANG Junna, HAN Chaochen, CHEN Jiawei, ZHAO Xiaoyan, YUAN Peiyan

Zdroj: Jisuanji gongcheng, Vol 50, Iss 10, Pp 266-280 (2024)

Témata: edge computing(ec), edge server(es) deployment, service placement, k-means clustering algorithm, multi-agent reinforcement learning algorithm, Computer engineering. Computer hardware, TK7885-7895, Computer software, QA76.75-76.765

Popis souboru: electronic resource

Relation: https://www.ecice06.com/fileup/1000-3428/PDF/20241024.pdf; https://doaj.org/toc/1000-3428

Přístupová URL adresa: https://doaj.org/article/caf49c3a82cb4db7a15e907b31f5e847

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

Autoři: Seyyed Morteza Ghamari Asma Aziz Mehrdad Ghahramani

Zdroj: Energies, Vol 18, Iss 18, p 4941 (2025)

Témata: power converters, backstepping method, nonlinear stability, reinforcement learning algorithm, grey wolf optimization, hardware-in-loop testing, Technology

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1996-1073/18/18/4941; https://doaj.org/toc/1996-1073

Přístupová URL adresa: https://doaj.org/article/4269c3cfa68a41cea76a6f068358a0b7

A Reinforcement Learning Solution for Queue Management in Public Utility Services

Autoři: Todor Dobrev Miroslav Markov Valentina Markova

Zdroj: Engineering Proceedings, Vol 104, Iss 1, p 6 (2025)

Témata: queueing system, reinforcement learning algorithm, Q-learning, utility services, Engineering machinery, tools, and implements, TA213-215

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2673-4591/104/1/6; https://doaj.org/toc/2673-4591

Přístupová URL adresa: https://doaj.org/article/65c58a44c5154f7882cc867aba3a49ab

Multi-agent Cooperative Algorithm for Obstacle Clearance Based on Deep Deterministic PolicyGradient and Attention Critic

Autoři: WANG Xianwei, FENG Xiang, YU Huiqun

Zdroj: Jisuanji kexue, Vol 51, Iss 7, Pp 319-326 (2024)

Témata: reinforcement learning algorithm, markov decision process, multi-agent cooperative control, dynamic obstacle clea-rance, attention mechanism, Computer software, QA76.75-76.765, Technology (General), T1-995

Popis souboru: electronic resource

Relation: https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2024-51-7-319.pdf; https://doaj.org/toc/1002-137X

Přístupová URL adresa: https://doaj.org/article/f8db4b6dd6b94fa585579adea5b780f1

Robust Deep Reinforcement Learning Algorithm for VNF-FG Embedding

Autoři: Bouroudi, Abdelmounaim Outtagarts, Abdelkader Hadjadj-Aoul, Yassine a další

Přispěvatelé: Bouroudi, Abdelmounaim Outtagarts, Abdelkader Hadjadj-Aoul, Yassine a další

Zdroj: 2022 IEEE 47th Conference on Local Computer Networks (LCN). :351-354

Témata: Deep Reinforcement Learning, [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], B5G/6G, Algorithm Selection, 0202 electrical engineering, electronic engineering, information engineering, Virtual Network Embedding Deep Reinforcement Learning Algorithm Selection Stationary bandit B5G/6G, 02 engineering and technology, Stationary bandit, Virtual Network Embedding

Popis souboru: application/pdf

Přístupová URL adresa: https://inria.hal.science/hal-03911352v1
https://inria.hal.science/hal-03911352v1/document
https://doi.org/10.1109/lcn53696.2022.9843650

Automatic voltage control considering demand response: Approximatively completed observed Markov decision process-based reinforcement learning scheme

Autoři: Yaru Gu Xueliang Huang

Zdroj: International Journal of Electrical Power & Energy Systems, Vol 161, Iss , Pp 110156- (2024)

Témata: Automatic voltage control, Partially observable system, Uncertainty, Differential increment incentive mechanism, Reinforcement learning algorithm, Production of electric energy or power. Powerplants. Central stations, TK1001-1841

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S0142061524003776; https://doaj.org/toc/0142-0615

Přístupová URL adresa: https://doaj.org/article/8c663f7a40fc409ba700143d61179495

Low-carbon economic dispatch strategy for integrated electrical and gas system with GCCP based on multi-agent deep reinforcement learning

Autoři: Wentao Feng Bingyan Deng Ziwen Zhang a další

Zdroj: Frontiers in Energy Research, Vol 12 (2024)

Témata: GCCP, 13. Climate action, integrated electrical and gas system, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, carbon emission, 02 engineering and technology, multi-agent deep reinforcement learning algorithm, low-carbon, 7. Clean energy, General Works, 12. Responsible consumption

Přístupová URL adresa: https://doaj.org/article/e2bfbac0d64f4f6eb72dfddab8d3ad7d

ADAS-RL: Safety learning approach for stable autonomous driving

Autoři: Dongsu Lee Minhae Kwon

Zdroj: ICT Express, Vol 8, Iss 3, Pp 479-483 (2022)

Témata: Autonomous vehicle, 0209 industrial biotechnology, Deep reinforcement learning algorithm, 0502 economics and business, 05 social sciences, Information technology, 02 engineering and technology, T58.5-58.64, Markov decision process

Přístupová URL adresa: https://doaj.org/article/01eb636b438140e29f04628d4b470752

An Applied Deep Reinforcement Learning Approach to Control Active Networked Microgrids in Smart Cities with Multi-Level Participation of Battery Energy Storage System and Electric Vehicles

Autoři: Reza Sepehrzad Amir Saman Godazi Langeroudi Amin Khodadadi a další

Zdroj: Sepehrzad, R, Godazi Langeroudi, A S, Khodadadi, A, Adinehpour, S, Al-Durra, A & Anvari-Moghaddam, A 2024, 'An Applied Deep Reinforcement Learning Approach to Control Active Networked Microgrids in Smart Cities with Multi-Level Participation of Battery Energy Storage System and Electric Vehicles', Sustainable Cities and Society, vol. 107, 105352, pp. 1-21. https://doi.org/10.1016/j.scs.2024.105352

Témata: name=SDG 7 - Affordable and Clean Energy, Electric vehicles, Deep reinforcement learning algorithm, 11. Sustainability, Energy management, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, name=SDG 17 - Partnerships for the Goals, name=SDG 9 - Industry, Innovation, and Infrastructure, 7. Clean energy, Networked microgrid

Popis souboru: application/pdf

Přístupová URL adresa: https://vbn.aau.dk/da/publications/946bd639-b3d2-457c-b769-dde5e83fe3f1
http://www.scopus.com/inward/record.url?scp=85191004487&partnerID=8YFLogxK
https://doi.org/10.1016/j.scs.2024.105352
https://vbn.aau.dk/ws/files/766592800/1-s2.0-S221067072400180X-main.pdf

Admission control policy and key agreement based on anonymous identity in cloud computing

Autoři: D. Paulraj S. Neelakandan M. Prakash a další

Zdroj: Journal of Cloud Computing: Advances, Systems and Applications, Vol 12, Iss 1, Pp 1-18 (2023)

Témata: Cloud computing, Cross-cloud data migration, Key agreement, Multi-agent reinforcement learning algorithm (MARL), Admission control policy (ACP), Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2192-113X

Přístupová URL adresa: https://doaj.org/article/a04a8ed3ebef47c38328e3392191fc99

FlexSim-Simulated PCB Assembly Line Optimization Using Deep Q-Network

Autoři: Jinhao Du Jabir Mumtaz Wenxi Zhao a další

Zdroj: Engineering Proceedings, Vol 75, Iss 1, p 34 (2024)

Témata: printed circuit board, FlexSim simulation, PCB assembly line, deep reinforcement learning algorithm, Engineering machinery, tools, and implements, TA213-215

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2673-4591/75/1/34; https://doaj.org/toc/2673-4591

Přístupová URL adresa: https://doaj.org/article/6026ca6b98214645808761998518604b