GenFedRL: a general federated reinforcement learning framework for deep reinforcement learning agents [PDF]
, 2023 To solve the problem that intelligent devices equipped with deep reinforcement learning agents lack effective security data sharing mechanisms in the intelligent Internet of things, a general federated reinforcement learning (GenFedRL) framework was ...
Biao JIN +4 more
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QL-STCT: an intelligent routing convergence method for SDN link failure [PDF]
, 2022 Aiming at the problem of routing convergence when SDN link failure occurs, a Q-Learning sub-topological convergence technique (QL-STCT) was proposed to realize intelligent route convergence when SDN links fail.Firstly, some nodes were selected in the ...
Chao CHEN +7 more
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Off-policy Maximum Entropy Deep Reinforcement Learning Algorithm Based on RandomlyWeighted Triple Q -Learning [PDF]
, 2022 Reinforcement learning is an important branch of machine learning.With the development of deep learning,deep reinforcement learning research has gradually developed into the focus of reinforcement learning research.Model-free off-policy deep ...
FAN Jing-yu, LIU Quan
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Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning [PDF]
, 2022 In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the ...
Fengyu WANG +5 more
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Edge intelligence-assisted routing protocol for Internet of vehicles via reinforcement learning [PDF]
, 2023 To achieve a highly reliable and adaptive packet routing protocol in a complex urban Internet of vehicles, an end-edge-cloud edge intelligence architecture was proposed which consisted of an end user layer, an edge collaboration layer, and a cloud ...
Bingyi LIU +5 more
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Survey on reinforcement learning based adaptive bit rate algorithm for mobile video streaming services [PDF]
, 2021 In recent years, with the continuous release of HTTP adaptive streaming (HAS) video datasets and network trace datasets, the machine learning methods, such as deep learning and reinforcement learning, have been continuously applied to adaptive bit rate ...
Jiafeng LI +4 more
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Research progress of deep reinforcement learning applied to text generation [PDF]
, 2020 With the recent exciting achievements of Google’s artificial intelligence system in the game of Go, deep reinforcement learning (DRL) has witnessed considerable development.
Cong XU +4 more
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Scheduling framework based on reinforcement learning in online-offline colocated cloud environment [PDF]
, 2023 Some reinforcement learning-based scheduling algorithms for cloud computing platforms barely considered one scenario or ignored the resource constraints of jobs and treated all machines as the same type, which caused low resource utilization or ...
Guanchen GUO +6 more
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Reinforcement learning-based detection method for malware behavior in industrial control systems [PDF]
, 2020 Due to the popularity of intelligent mobile devices, malwares in the internet have seriously threatened the security of industrial control systems. Increasing number of malware attacks has become a major concern in the information security community ...
Feng XIE +7 more
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Study on Intelligent Recommendation Method of Dueling Network Reinforcement Learning Based on Regret Exploration [PDF]
, 2022 In recent years,the application of deep reinforcement learning in recommendation system has attracted much attention.Based on the existing research,this paper proposes a new recommendation model RP-Dueling,which is based on the deep reinforcement ...
HONG Zhi-li, LAI Jun, CAO Lei, CHEN Xi-liang, XU Zhi-xiong
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