Enhancing Digital Twins through Reinforcement Learning
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/8827189/8842826/08842888.pdf?arnumber=8842888
Cited by 41 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Adaptive Scheduling In Dynamic Environments: A Data-Driven Approach With Digital Twins And Deep Reinforcement Learning;2023 IEEE 3rd International Conference on Digital Twins and Parallel Intelligence (DTPI);2023-11-07
2. A Comprehensive Review of Digital Twin from the Perspective of Total Process: Data, Models, Networks and Applications;Sensors;2023-10-08
3. A Bayesian Framework for Digital Twin-Based Control, Monitoring, and Data Collection in Wireless Systems;IEEE Journal on Selected Areas in Communications;2023-10
4. A Model-Driven Platform for Engineering Holistic Digital Twins;2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C);2023-10-01
5. Requirements and design patterns for adaptive, autonomous, and context-aware digital twins in industry 4.0 digital factories;Computers in Industry;2023-08
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