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12/24/2022
Structure-Enhanced DRL for Optimal Transmission Scheduling
Remote state estimation of large-scale distributed dynamic processes pla...
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12/16/2022
Innovation-Based Remote State Estimation Secrecy with no Acknowledgments
Secrecy encoding for remote state estimation in the presence of adversar...
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11/20/2022
Structure-Enhanced Deep Reinforcement Learning for Optimal Transmission Scheduling
Remote state estimation of large-scale distributed dynamic processes pla...
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10/03/2022
Deep Learning for Wireless Networked Systems: a joint Estimation-Control-Scheduling Approach
Wireless networked control system (WNCS) connecting sensors, controllers...
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07/18/2022
Bayesian Quickest Change Detection of an Intruder in Acknowledgments for Private Remote State Estimation
For geographically separated cyber-physical systems, state estimation at...
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05/19/2022
Centralized Model-Predictive Control with Human-Driver Interaction for Platooning
Cooperative adaptive cruise control presents an opportunity to improve r...
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03/31/2022
Remote State Estimation of Multiple Systems over Semi-Markov Wireless Fading Channels
This work studies remote state estimation of multiple linear time-invari...
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09/26/2021
Deep Reinforcement Learning for Wireless Scheduling in Distributed Networked Control
In the literature of transmission scheduling in wireless networked contr...
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04/09/2021
Remote State Estimation of Multiple Systems over Multiple Markov Fading Channels
We consider remote state estimation of multiple discrete-time linear tim...
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12/02/2020
Anytime Control with Markovian Computation and Communication Resources
We investigate a novel anytime algorithm for wireless networked control ...
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05/16/2020
Remote State Estimation with Smart Sensors over Markov Fading Channels
We consider a fundamental remote state estimation problem of discrete-ti...
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11/01/2019
A Game-Theoretic Approach to Covert Communications
This paper considers a game-theoretic formulation of the covert communic...
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05/15/2019
Deep reinforcement learning for scheduling in large-scale networked control systems
This work considers the problem of control and resource scheduling in ne...
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03/08/2018
DeepCAS: A Deep Reinforcement Learning Algorithm for Control-Aware Scheduling
We consider networked control systems consisting of multiple independent...
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02/22/2018
Asynchronous stochastic approximations with asymptotically biased errors and deep multi-agent learning
Asynchronous stochastic approximations are an important class of model-f...
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10/15/2017