Repot: Transferable Reinforcement Learning for Quality-Centric Networked Monitoring in Various Environments
Collecting and monitoring data in low-latency from numerous sensing devices is one of the key foundations in networked cyber-physical applications such as industrial process control, intelligent traffic control, and networked robots. As the delay in data updates can degrade the quality of networked...
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| Main Authors: | , , , , |
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| Format: | article |
| Language: | EN |
| Published: |
IEEE
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/5896d7e1f2a54ae19ade84d6d7ca88b2 |
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