Deep reinforcement learning sensor scheduling for effective monitoring of dynamical systems

Deep reinforcement learning sensor scheduling for effective monitoring of dynamical systems

Advances in technology have enabled the use of sensors with varied modalities to monitor different parts of systems, each providing diverse levels of information about the underlying system. However, resource limitations and computational power restrict the number of sensors/data that can be process...

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Bibliographic Details
Main Authors:	Mohammad Alali, Armita Kazeminajafabadi, Mahdi Imani
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2024-12-01
Series:	Systems Science & Control Engineering
Subjects:	Sensor scheduling monitoring hidden Markov models state estimation reinforcement learning
Online Access:	https://www.tandfonline.com/doi/10.1080/21642583.2024.2329260
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