Results 21 to 30 of about 2,973 (161)
Research on power allocation of integrated VLPC based on deep reinforcement learning [PDF]
, 2022 A power allocation scheme for integrated visible light position and communication (VLPC) system based on deep reinforcement learning was proposed to achieve power allocation for communication positioning integration.First, the frame structure design of ...
Bing LI +7 more
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Deep reinforcement learning-based resource reservation algorithm for emergency Internet-of-things slice [PDF]
, 2020 Based on the requirements of ultra-low latency services for emergency Internet-of-things (EIoT) applications,a multi-slice network architecture for ultra-low latency emergency IoT was designed,and a general methodology framework based on resource ...
Guisong LIU, Guolin SUN, Ruijie OU
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Guangtongxin yanjiu, 2021 在大力发展智能电网的背景下，支撑电网运转的电力光通信网规模日趋庞大，其承载的业务更加多样化。然而电力光通信网的业务路由规划主要以最短路径算法为主，导致电力光通信网存在业务重要度分布不均衡，从而导致网络局部风险过高的问题。针对上述现状，文章采用深度强化学习技术，以网络业务风险均衡为目标，提出了基于强化学习的电力光通信网风险均衡路由算法。该算法考虑业务重要度分布情况、链路容量和链路光信噪比，实现了电力光通信网风险均衡化。文章选取某省电力通信子网验证方案的有效性，研究结果表明 ...
张庚 +5 more
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Research on mobile edge computing and caching in massive wireless communication network [PDF]
, 2021 For the large-scale network mobile edge computing and caching technology of future 6G mobile communications, firstly, the architectures and principles of mobile edge computing and caching in large-scale wireless networks were introduced, and the ...
Chong ZHENG +3 more
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智能科学与技术学报, 2022 群体行为往往能产生远超个体行为的价值和复杂度。为了在个体智能的基础上更有效地衍生出群体智能，需要基于群体熵来科学地衡量群体智能水平，并以群体熵为引导目标，推动群体智能的增强和演进。针对这个重要的科学问题，以无人小车群体为研究对象，提出基于参数共享和群体策略熵的多智能体soft Q learning算法，通过共享智能体的观测信息，并结合最大熵强化学习方法，实现探索型任务中群体策略的持续学习更新。同时，通过将群体熵定义为度量工具，刻画群体学习中熵变化模式，实现对群智汇聚过程的定量分析。
冯埔 +4 more
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Software-defined networking QoS optimization based on deep reinforcement learning [PDF]
, 2019 To solve the problem that the QoS optimization schemes which based on heuristic algorithm degraded often due to the mismatch between parameters and network characteristics in software-defined networking scenarios,a software-defined networking QoS ...
Julong LAN +3 more
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Joint optimization of edge computing and caching in NDN [PDF]
, 2022 Named data networking (NDN) is architecturally easier to integrate with edge computing as its routing is based on content names and its nodes have caching capabilities.Firstly, an integrated framework was proposed for implementing dynamic coordination of
Min CHENG, Yu ZHANG
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智能科学与技术学报, 2020 深度强化学习主要被用来处理感知-决策问题，已经成为人工智能领域重要的研究分支。概述了基于值函数和策略梯度的两类深度强化学习算法，详细阐述了深度Q网络、深度策略梯度及相关改进算法的原理，并综述了深度强化学习在视频游戏、导航、多智能体协作以及推荐系统等领域的应用研究进展。最后，对深度强化学习的算法和应用进行展望，针对一些未来的研究方向和研究热点给出了建议。
刘朝阳, 穆朝絮, 孙长银
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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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智能科学与技术学报, 2020 研究了基于深度强化学习算法的自主式水下航行器（AUV）深度控制问题。区别于传统的控制算法，深度强化学习方法让航行器自主学习控制律，避免人工建立精确模型和设计控制律。采用深度确定性策略梯度方法设计了actor与critic两种神经网络。actor神经网络给出控制策略，critic神经网络用于评估该策略，AUV的深度控制可以通过训练这两个神经网络实现。在OpenAI Gym平台上仿真验证了算法的有效性。
王日中, 李慧平, 崔迪, 徐德民
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