Results 111 to 120 of about 5,206 (257)
物联网学报随着物联网（IoT, internet of things）基站的部署愈发密集，网络干扰管控的重要性愈发凸显。物联网中，设备常采用随机接入，以分布式的方式接入信道。在海量设备的物联网场景中，节点之间可能会出现严重的干扰，导致网络的吞吐量性能严重下降。为了解决随机接入网络中的干扰管控问题，考虑基于协作接收的多基站时隙Aloha网络，利用强化学习工具，设计自适应传输算法，实现干扰管控，优化网络的吞吐量性能，并提高网络的公平性。首先，设计了基于Q-学习的自适应传输算法 ...
黄元康1，詹文1，孙兴华2
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Vertical handover policy for cyber-physical systems aided by SAGIN based on deep reinforcement learning [PDF]
The vertical handover policy of space-air-ground integrated cyber-physical systems based on deep reinforcement learning was studied, in which the challenges of complicated network model and difficulties in acquiring prior knowledge for network topology ...
LEUNG Victor C.M. +4 more
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实时电价机制下基于复合两端采样强化学习的区域供冷系统需求响应运行控制
Scientia Sinica Technologica, 2023 Y. Song, Peipei Yu, Hongcai Zhang
semanticscholar +1 more source
Intelligent anti-jamming decision algorithm based on proximal policy optimization [PDF]
The existing intelligent anti-jamming methods based on deep reinforcement learning are applied to space-ground TT&C and communication links, in which the deep neural network used for decision-making has a complex structure, and the resources of ...
HUANG Wei +4 more
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Graph-to-sequence deep reinforcement learning based complex task deployment strategy in MEC [PDF]
With the help of mobile edge computing (MEC) and network virtualization technology, the mobile terminals can offload the computing, storage, transmission and other resource required for executing various complex applications to the edge service nodes ...
Mintao CAO +4 more
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Recursive deep reinforcement learning-based collaborative caching relay algorithm in mobile vehicular edge network [PDF]
Considering scenarios without road side unit coverage, a recursive deep reinforcement learning-based collaborative caching relay algorithm was proposed to construct a caching system by leveraging the cooperation among vehicles.
MA Huahong +3 more
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Guangtongxin yanjiu, 2010 在基于恰量时间（Just-Enough-Time,JET）信令的无光缓存光突发交换（OBS）网络中,根据网络负载和服务质量（QoS）要求灵活进行偏置时间（Offset Time,OT）设置的问题,文章提出了一种使用增强型学习机制计算OT的算法,使得OT能够随着网络载荷的变化进行自适应调整,并能支持QoS,从而能较好地适应网络状态的变化。仿真结果表明,该算法可以在不同的网络状态下有效地降低端到端的延迟和阻塞率,并能很好地提供QoS服务。
孙万举, 朱娜, 董传成
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Fast deep reinforcement learning anti-jamming algorithm based on similar sample generation [PDF]
To improve the learning efficiency of anti-jamming algorithms based on deep reinforcement learning and enable them to adapt more quickly to unknown jamming environments, a fast deep reinforcement learning anti-jamming algorithm based on similar sample ...
NIU Yingtao, ZHOU Quan
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智能科学与技术学报, 2020 总结了国内外人工智能技术在游戏领域的研究进展，分析了游戏领域的研究进步对于现实社会的意义。针对强化学习中免模型方法存在的仿真与真实的鸿沟、基于模型的方法缺乏通用性的问题，提出平行博弈的思想和方法，介绍了平行博弈在解决现有单角色博弈和多角色博弈问题上的先进之处。认为虚实结合的平行博弈方法将成为迈向通用人工智能的奠基石。
沈宇, 韩金朋, 李灵犀, 王飞跃
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