知识 发表于 2025-3-26 22:57:52
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Deep Reinforcement Learning for Mobile Edge Computing Systemsblem for minimizing the task delay and the ratio of dropped tasks. We propose a deep Q-learning-based algorithm that enables the mobile devices to make their task offloading decisions in a decentralized fashion with local information. This algorithm incorporates double deep Q-network (DQN) and dueliFacet-Joints 发表于 2025-3-27 12:59:34
Mobile Computation Offloading with Hard Task Completion Timesn number of parts, each part is uploaded separately, and a MultiOpt algorithm is used to decide the upload initiation time of each part during runtime. The problem is studied for homogeneous Markovian wireless channels, and energy optimality is proved for the OnOpt algorithm based on continuous uploHERTZ 发表于 2025-3-27 14:08:43
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https://doi.org/10.1007/978-3-658-35823-5 “official retirement date” was in 2001. Since he joined the Department of Electrical and Computer Engineering at the University of Waterloo in 1970 and served as its chair from 1984–1990, Prof. Mark has helped and influenced thousands of students and colleagues, and contributed to the growing reput耕种 发表于 2025-3-28 02:26:05
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