… Abstract: To solve the problem of sensor management in the optimization of extended target
tracking, this paper proposes a sensor management method based on deep reinforcement …

… At the edge-device layer, edge servers act as intermediaries, using the multi-dimensional …
Then, multi-agent deep reinforcement learning (MADRL) is used to incrementally approach …

… of new energy output, we propose a new energy storage adaptive control strategy for primary
… Primary frequency control of renewable energy based on deep reinforcement learning[C]// …

… Due to the powerful learning ability, deep learning networks can not only discover physical
laws but also solve partial differential equations (… Deep learning-based numerical methods …

… The main reason for proposing an unsupervised learning-based algorithm is that we have
independently located airplanes with unstructured characteristics in AANETs before forming …

… Considering the multidimensional resource constraints, eg, computing power, storage, and
bandwidth, with the objective of minimizing task processing latency, the joint optimization of …

… , edge caching, multi-dimensional resource allocation, user … issue, a federated learning
based privacy-preserving scheme … mobile-edge computing with energy harvesting devices[J]. …

… 2016 年,Mao 等人[14]通过能量收集(Energy Harvesting, EH)… 同年,深度强化学习(Deep
Reinforcement Learning, DRL)与… 的卸载 (Deep Meta Reinforcement Learning-based Offloading, …

本文在综述太阳系边际探测的发展历程和现状基础上, 基于太阳系边际探测的发展趋势, 阐释了
太阳系边际探测的4 类科学目标, 提出了我国太阳系边际探测的总体目标, 阶段目标及近期探测…

… WANG Baoxian, JIAN Jigui, SHEN Yanjun 1110 Delay-dependent finite-time Hю filtering for
networked control systems: A switched system approach ........... WU YuanQing, SU Hongye, …