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In: <i>2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)</i>. IEEE; 2023. doi:<a href=\"https://doi.org/10.1109/iros55552.2023.10341937\">10.1109/iros55552.2023.10341937</a>","bibtex":"@inproceedings{le Fevre Sejersen_Kayacan_2023, title={CAMETA: Conflict-Aware Multi-Agent Estimated Time of Arrival Prediction for Mobile Robots}, DOI={<a href=\"https://doi.org/10.1109/iros55552.2023.10341937\">10.1109/iros55552.2023.10341937</a>}, booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, publisher={IEEE}, author={le Fevre Sejersen, Jonas and Kayacan, Erdal}, year={2023} }","mla":"le Fevre Sejersen, Jonas, and Erdal Kayacan. “CAMETA: Conflict-Aware Multi-Agent Estimated Time of Arrival Prediction for Mobile Robots.” <i>2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)</i>, IEEE, 2023, doi:<a href=\"https://doi.org/10.1109/iros55552.2023.10341937\">10.1109/iros55552.2023.10341937</a>."}},{"publication_status":"published","date_updated":"2023-01-09T16:47:00Z","intvolume":"        40","year":"2022","title":"Behavioral Economics for Human-in-the-Loop Control Systems Design: Overconfidence and the Hot Hand Fallacy","author":[{"last_name":"Protte","first_name":"Marius","full_name":"Protte, Marius"},{"first_name":"Rene","last_name":"Fahr","full_name":"Fahr, Rene"},{"first_name":"Daniel E.","last_name":"Quevedo","full_name":"Quevedo, Daniel E."}],"publication_identifier":{"issn":["1066-033X","1941-000X"]},"doi":"10.1109/mcs.2020.3019723","language":[{"iso":"eng"}],"issue":"6","publication":"IEEE Control Systems","type":"journal_article","keyword":["Electrical and Electronic Engineering","Modeling and Simulation","Control and Systems Engineering","Electrical and Electronic Engineering","Modeling and Simulation","Control and Systems Engineering"],"department":[{"_id":"57"}],"date_created":"2023-01-09T16:46:46Z","status":"public","user_id":"158","volume":40,"page":"57-76","publisher":"Institute of Electrical and Electronics Engineers (IEEE)","_id":"35586","citation":{"mla":"Protte, Marius, et al. “Behavioral Economics for Human-in-the-Loop Control Systems Design: Overconfidence and the Hot Hand Fallacy.” <i>IEEE Control Systems</i>, vol. 40, no. 6, Institute of Electrical and Electronics Engineers (IEEE), 2022, pp. 57–76, doi:<a href=\"https://doi.org/10.1109/mcs.2020.3019723\">10.1109/mcs.2020.3019723</a>.","bibtex":"@article{Protte_Fahr_Quevedo_2022, title={Behavioral Economics for Human-in-the-Loop Control Systems Design: Overconfidence and the Hot Hand Fallacy}, volume={40}, DOI={<a href=\"https://doi.org/10.1109/mcs.2020.3019723\">10.1109/mcs.2020.3019723</a>}, number={6}, journal={IEEE Control Systems}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Protte, Marius and Fahr, Rene and Quevedo, Daniel E.}, year={2022}, pages={57–76} }","ama":"Protte M, Fahr R, Quevedo DE. 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A\r\nsensor takes measurements of the system output and forwards its dynamic state\r\nestimates to a remote controller over a packet-dropping link. The controller\r\ndetermines the optimal control law for the process using the estimates it\r\nreceives. An attacker aims at degrading the control performance by increasing\r\nthe packet-dropout rate with a DoS attack towards the sensor-controller\r\nchannel. We assume both the controller and the attacker are rational in a\r\ngame-theoretic sense and establish a partially observable stochastic game to\r\nderive the optimal joint design of scheduling and control. Using dynamic\r\nprogramming we prove that the control and scheduling policies can be designed\r\nseparately without sacrificing optimality, making the problem equivalent to a\r\ncomplete information game. We employ Nash Q-learning to solve the problem and\r\nprove that the solution is guaranteed to constitute an $\\epsilon$-Nash\r\nequilibrium. Numerical examples are provided to illustrate the tradeoffs\r\nbetween control performance and communication cost.","lang":"eng"}],"citation":{"bibtex":"@article{Lu_Quevedo_2021, title={A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks}, journal={arXiv:2103.05893}, author={Lu, Jingyi and Quevedo, Daniel E.}, year={2021} }","ama":"Lu J, Quevedo DE. A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks. <i>arXiv:210305893</i>. Published online 2021.","mla":"Lu, Jingyi, and Daniel E. Quevedo. “A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks.” <i>ArXiv:2103.05893</i>, 2021.","chicago":"Lu, Jingyi, and Daniel E. Quevedo. “A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks.” <i>ArXiv:2103.05893</i>, 2021.","short":"J. Lu, D.E. Quevedo, ArXiv:2103.05893 (2021).","ieee":"J. Lu and D. E. Quevedo, “A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks,” <i>arXiv:2103.05893</i>. 2021.","apa":"Lu, J., &#38; Quevedo, D. E. (2021). A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks. In <i>arXiv:2103.05893</i>."},"publication":"arXiv:2103.05893","user_id":"158","_id":"35588","language":[{"iso":"eng"}],"date_updated":"2023-01-09T18:04:57Z","author":[{"full_name":"Lu, Jingyi","last_name":"Lu","first_name":"Jingyi"},{"full_name":"Quevedo, Daniel E.","first_name":"Daniel E.","last_name":"Quevedo"}],"title":"A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks","year":"2021","status":"public"},{"date_created":"2022-01-28T14:11:04Z","department":[{"_id":"52"},{"_id":"57"}],"type":"journal_article","citation":{"chicago":"Heid, Stefan, Daniel Weber, Henrik Bode, Eyke Hüllermeier, and Oliver Wallscheid. “OMG: A Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control.” <i>Journal of Open Source Software</i> 5, no. 54 (2020): 2435.","short":"S. Heid, D. Weber, H. Bode, E. Hüllermeier, O. Wallscheid, Journal of Open Source Software 5 (2020) 2435.","ieee":"S. Heid, D. Weber, H. Bode, E. Hüllermeier, and O. Wallscheid, “OMG: A scalable and flexible simulation and testing environment toolbox for intelligent microgrid control,” <i>Journal of Open Source Software</i>, vol. 5, no. 54, p. 2435, 2020.","apa":"Heid, S., Weber, D., Bode, H., Hüllermeier, E., &#38; Wallscheid, O. (2020). OMG: A scalable and flexible simulation and testing environment toolbox for intelligent microgrid control. <i>Journal of Open Source Software</i>, <i>5</i>(54), 2435.","bibtex":"@article{Heid_Weber_Bode_Hüllermeier_Wallscheid_2020, title={OMG: A scalable and flexible simulation and testing environment toolbox for intelligent microgrid control}, volume={5}, number={54}, journal={Journal of Open Source Software}, author={Heid, Stefan and Weber, Daniel and Bode, Henrik and Hüllermeier, Eyke and Wallscheid, Oliver}, year={2020}, pages={2435} }","ama":"Heid S, Weber D, Bode H, Hüllermeier E, Wallscheid O. OMG: A scalable and flexible simulation and testing environment toolbox for intelligent microgrid control. <i>Journal of Open Source Software</i>. 2020;5(54):2435.","mla":"Heid, Stefan, et al. “OMG: A Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control.” <i>Journal of Open Source Software</i>, vol. 5, no. 54, 2020, p. 2435."},"issue":"54","publication":"Journal of Open Source Software","_id":"29649","language":[{"iso":"eng"}],"page":"2435","volume":5,"user_id":"11291","author":[{"id":"39640","full_name":"Heid, Stefan","first_name":"Stefan","last_name":"Heid","orcid":"0000-0002-9461-7372"},{"id":"24041","last_name":"Weber","first_name":"Daniel","orcid":"0000-0003-3367-5998","full_name":"Weber, Daniel"},{"last_name":"Bode","first_name":"Henrik","full_name":"Bode, Henrik","id":"40880"},{"full_name":"Hüllermeier, Eyke","first_name":"Eyke","last_name":"Hüllermeier"},{"last_name":"Wallscheid","first_name":"Oliver","orcid":"https://orcid.org/0000-0001-9362-8777","full_name":"Wallscheid, Oliver","id":"11291"}],"title":"OMG: A scalable and flexible simulation and testing environment toolbox for intelligent microgrid control","status":"public","year":"2020","intvolume":"         5","date_updated":"2022-03-02T07:16:15Z"},{"language":[{"iso":"eng"}],"doi":"10.1002/rnc.4910","author":[{"last_name":"Lu","first_name":"Jingyi","full_name":"Lu, Jingyi"},{"full_name":"Leong, Alex S.","first_name":"Alex S.","last_name":"Leong"},{"full_name":"Quevedo, Daniel E.","first_name":"Daniel E.","last_name":"Quevedo"}],"publication_identifier":{"issn":["1049-8923","1099-1239"]},"year":"2020","title":"Optimal event‐triggered transmission scheduling for privacy‐preserving wireless state estimation","intvolume":"        30","date_updated":"2023-01-09T16:46:29Z","publication_status":"published","date_created":"2023-01-09T16:46:15Z","department":[{"_id":"57"}],"keyword":["Electrical and Electronic Engineering","Industrial and Manufacturing Engineering","Mechanical Engineering","Aerospace Engineering","Biomedical Engineering","General Chemical Engineering","Control and Systems Engineering"],"type":"journal_article","publication":"International Journal of Robust and Nonlinear Control","issue":"11","publisher":"Wiley","_id":"35585","page":"4205-4224","volume":30,"user_id":"158","status":"public","citation":{"short":"J. Lu, A.S. Leong, D.E. Quevedo, International Journal of Robust and Nonlinear Control 30 (2020) 4205–4224.","chicago":"Lu, Jingyi, Alex S. Leong, and Daniel E. Quevedo. “Optimal Event‐triggered Transmission Scheduling for Privacy‐preserving Wireless State Estimation.” <i>International Journal of Robust and Nonlinear Control</i> 30, no. 11 (2020): 4205–24. <a href=\"https://doi.org/10.1002/rnc.4910\">https://doi.org/10.1002/rnc.4910</a>.","apa":"Lu, J., Leong, A. S., &#38; Quevedo, D. E. (2020). Optimal event‐triggered transmission scheduling for privacy‐preserving wireless state estimation. <i>International Journal of Robust and Nonlinear Control</i>, <i>30</i>(11), 4205–4224. <a href=\"https://doi.org/10.1002/rnc.4910\">https://doi.org/10.1002/rnc.4910</a>","ieee":"J. Lu, A. S. Leong, and D. E. Quevedo, “Optimal event‐triggered transmission scheduling for privacy‐preserving wireless state estimation,” <i>International Journal of Robust and Nonlinear Control</i>, vol. 30, no. 11, pp. 4205–4224, 2020, doi: <a href=\"https://doi.org/10.1002/rnc.4910\">10.1002/rnc.4910</a>.","ama":"Lu J, Leong AS, Quevedo DE. Optimal event‐triggered transmission scheduling for privacy‐preserving wireless state estimation. <i>International Journal of Robust and Nonlinear Control</i>. 2020;30(11):4205-4224. doi:<a href=\"https://doi.org/10.1002/rnc.4910\">10.1002/rnc.4910</a>","bibtex":"@article{Lu_Leong_Quevedo_2020, title={Optimal event‐triggered transmission scheduling for privacy‐preserving wireless state estimation}, volume={30}, DOI={<a href=\"https://doi.org/10.1002/rnc.4910\">10.1002/rnc.4910</a>}, number={11}, journal={International Journal of Robust and Nonlinear Control}, publisher={Wiley}, author={Lu, Jingyi and Leong, Alex S. and Quevedo, Daniel E.}, year={2020}, pages={4205–4224} }","mla":"Lu, Jingyi, et al. “Optimal Event‐triggered Transmission Scheduling for Privacy‐preserving Wireless State Estimation.” <i>International Journal of Robust and Nonlinear Control</i>, vol. 30, no. 11, Wiley, 2020, pp. 4205–24, doi:<a href=\"https://doi.org/10.1002/rnc.4910\">10.1002/rnc.4910</a>."}},{"date_updated":"2023-02-14T11:08:09Z","publication_status":"published","author":[{"full_name":"Noroozi, Navid","first_name":"Navid","last_name":"Noroozi"},{"last_name":"Jackson","first_name":"Roxanne","full_name":"Jackson, Roxanne"},{"full_name":"Quevedo, Daniel E.","first_name":"Daniel E.","last_name":"Quevedo"},{"full_name":"Wirth, Fabian R.","last_name":"Wirth","first_name":"Fabian R."},{"first_name":"Rolf","last_name":"Findeisen","full_name":"Findeisen, Rolf"}],"year":"2020","title":"On noise-to-state stability of stochastic discrete-time systems via finite-step Lyapunov functions","status":"public","doi":"10.1109/cdc40024.2019.9030178","user_id":"238","_id":"42073","language":[{"iso":"eng"}],"publisher":"IEEE","citation":{"apa":"Noroozi, N., Jackson, R., Quevedo, D. E., Wirth, F. R., &#38; Findeisen, R. (2020). On noise-to-state stability of stochastic discrete-time systems via finite-step Lyapunov functions. <i>2019 IEEE 58th Conference on Decision and Control (CDC)</i>. <a href=\"https://doi.org/10.1109/cdc40024.2019.9030178\">https://doi.org/10.1109/cdc40024.2019.9030178</a>","ieee":"N. Noroozi, R. Jackson, D. E. Quevedo, F. R. Wirth, and R. Findeisen, “On noise-to-state stability of stochastic discrete-time systems via finite-step Lyapunov functions,” 2020, doi: <a href=\"https://doi.org/10.1109/cdc40024.2019.9030178\">10.1109/cdc40024.2019.9030178</a>.","short":"N. Noroozi, R. Jackson, D.E. Quevedo, F.R. Wirth, R. Findeisen, in: 2019 IEEE 58th Conference on Decision and Control (CDC), IEEE, 2020.","chicago":"Noroozi, Navid, Roxanne Jackson, Daniel E. Quevedo, Fabian R. Wirth, and Rolf Findeisen. “On Noise-to-State Stability of Stochastic Discrete-Time Systems via Finite-Step Lyapunov Functions.” In <i>2019 IEEE 58th Conference on Decision and Control (CDC)</i>. IEEE, 2020. <a href=\"https://doi.org/10.1109/cdc40024.2019.9030178\">https://doi.org/10.1109/cdc40024.2019.9030178</a>.","mla":"Noroozi, Navid, et al. “On Noise-to-State Stability of Stochastic Discrete-Time Systems via Finite-Step Lyapunov Functions.” <i>2019 IEEE 58th Conference on Decision and Control (CDC)</i>, IEEE, 2020, doi:<a href=\"https://doi.org/10.1109/cdc40024.2019.9030178\">10.1109/cdc40024.2019.9030178</a>.","ama":"Noroozi N, Jackson R, Quevedo DE, Wirth FR, Findeisen R. On noise-to-state stability of stochastic discrete-time systems via finite-step Lyapunov functions. In: <i>2019 IEEE 58th Conference on Decision and Control (CDC)</i>. IEEE; 2020. doi:<a href=\"https://doi.org/10.1109/cdc40024.2019.9030178\">10.1109/cdc40024.2019.9030178</a>","bibtex":"@inproceedings{Noroozi_Jackson_Quevedo_Wirth_Findeisen_2020, title={On noise-to-state stability of stochastic discrete-time systems via finite-step Lyapunov functions}, DOI={<a href=\"https://doi.org/10.1109/cdc40024.2019.9030178\">10.1109/cdc40024.2019.9030178</a>}, booktitle={2019 IEEE 58th Conference on Decision and Control (CDC)}, publisher={IEEE}, author={Noroozi, Navid and Jackson, Roxanne and Quevedo, Daniel E. and Wirth, Fabian R. and Findeisen, Rolf}, year={2020} }"},"publication":"2019 IEEE 58th Conference on Decision and Control (CDC)","department":[{"_id":"57"}],"type":"conference","date_created":"2023-02-14T11:02:49Z"},{"date_created":"2023-02-14T11:10:42Z","department":[{"_id":"57"}],"type":"journal_article","citation":{"ieee":"K. Ding, X. Ren, D. E. Quevedo, S. Dey, and L. Shi, “Defensive deception against reactive jamming attacks in remote state estimation,” <i>Automatica</i>, vol. 113, 2020.","apa":"Ding, K., Ren, X., Quevedo, D. E., Dey, S., &#38; Shi, L. (2020). Defensive deception against reactive jamming attacks in remote state estimation. <i>Automatica</i>, <i>113</i>.","short":"K. Ding, X. Ren, D.E. Quevedo, S. Dey, L. Shi, Automatica 113 (2020).","chicago":"Ding, K., X. Ren, D. E. Quevedo, S. Dey, and L. Shi. “Defensive Deception against Reactive Jamming Attacks in Remote State Estimation.” <i>Automatica</i> 113 (2020).","mla":"Ding, K., et al. “Defensive Deception against Reactive Jamming Attacks in Remote State Estimation.” <i>Automatica</i>, vol. 113, 2020.","bibtex":"@article{Ding_Ren_Quevedo_Dey_Shi_2020, title={Defensive deception against reactive jamming attacks in remote state estimation}, volume={113}, journal={Automatica}, author={Ding, K. and Ren, X. and Quevedo, D. E. and Dey, S. and Shi, L.}, year={2020} }","ama":"Ding K, Ren X, Quevedo DE, Dey S, Shi L. Defensive deception against reactive jamming attacks in remote state estimation. <i>Automatica</i>. 2020;113."},"publication":"Automatica","language":[{"iso":"eng"}],"_id":"42074","volume":113,"user_id":"238","author":[{"first_name":"K.","last_name":"Ding","full_name":"Ding, K."},{"full_name":"Ren, X.","last_name":"Ren","first_name":"X."},{"full_name":"Quevedo, D. E.","first_name":"D. E.","last_name":"Quevedo"},{"first_name":"S.","last_name":"Dey","full_name":"Dey, S."},{"full_name":"Shi, L.","first_name":"L.","last_name":"Shi"}],"year":"2020","status":"public","title":"Defensive deception against reactive jamming attacks in remote state estimation","intvolume":"       113","date_updated":"2023-02-14T11:29:59Z"},{"citation":{"bibtex":"@article{Leong_Ramaswamy_Quevedo_Karl_Shi_2019, title={Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems}, DOI={<a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">10.1016/j.automatica.2019.108759</a>}, number={108759}, journal={Automatica}, author={Leong, Alex S. and Ramaswamy, Arunselvan and Quevedo, Daniel E. and Karl, Holger and Shi, Ling}, year={2019} }","ama":"Leong AS, Ramaswamy A, Quevedo DE, Karl H, Shi L. Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems. <i>Automatica</i>. 2019. doi:<a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">10.1016/j.automatica.2019.108759</a>","mla":"Leong, Alex S., et al. “Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber–Physical Systems.” <i>Automatica</i>, 108759, 2019, doi:<a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">10.1016/j.automatica.2019.108759</a>.","chicago":"Leong, Alex S., Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl, and Ling Shi. “Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber–Physical Systems.” <i>Automatica</i>, 2019. <a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">https://doi.org/10.1016/j.automatica.2019.108759</a>.","short":"A.S. Leong, A. Ramaswamy, D.E. Quevedo, H. Karl, L. Shi, Automatica (2019).","ieee":"A. S. Leong, A. Ramaswamy, D. E. Quevedo, H. Karl, and L. Shi, “Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems,” <i>Automatica</i>, 2019.","apa":"Leong, A. S., Ramaswamy, A., Quevedo, D. E., Karl, H., &#38; Shi, L. (2019). Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems. <i>Automatica</i>. <a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">https://doi.org/10.1016/j.automatica.2019.108759</a>"},"file_date_updated":"2020-01-31T15:57:50Z","project":[{"name":"Netzgewahre Regelung & regelungsgewahre Netze","_id":"24"}],"quality_controlled":"1","status":"public","has_accepted_license":"1","_id":"15741","user_id":"126","ddc":["000"],"publication":"Automatica","abstract":[{"lang":"eng","text":"\r\nIn many cyber–physical systems, we encounter the problem of remote state estimation of geo- graphically distributed and remote physical processes. This paper studies the scheduling of sensor transmissions to estimate the states of multiple remote, dynamic processes. Information from the different sensors has to be transmitted to a central gateway over a wireless network for monitoring purposes, where typically fewer wireless channels are available than there are processes to be monitored. For effective estimation at the gateway, the sensors need to be scheduled appropriately, i.e., at each time instant one needs to decide which sensors have network access and which ones do not. To address this scheduling problem, we formulate an associated Markov decision process (MDP). This MDP is then solved using a Deep Q-Network, a recent deep reinforcement learning algorithm that is at once scalable and model-free. We compare our scheduling algorithm to popular scheduling algorithms such as round-robin and reduced-waiting-time, among others. Our algorithm is shown to significantly outperform these algorithms for many example scenario"}],"date_created":"2020-01-31T15:55:27Z","file":[{"date_updated":"2020-01-31T15:57:50Z","relation":"main_file","file_size":"675382","access_level":"closed","file_name":"leoram20a.pdf","content_type":"application/pdf","success":1,"file_id":"15743","creator":"hkarl","date_created":"2020-01-31T15:57:50Z"}],"department":[{"_id":"7"},{"_id":"34"},{"_id":"3"},{"_id":"75"},{"_id":"57"}],"type":"journal_article","author":[{"first_name":"Alex S.","last_name":"Leong","full_name":"Leong, Alex S."},{"orcid":"https://orcid.org/ 0000-0001-7547-8111","first_name":"Arunselvan","last_name":"Ramaswamy","full_name":"Ramaswamy, Arunselvan","id":"66937"},{"last_name":"Quevedo","first_name":"Daniel E.","full_name":"Quevedo, Daniel E."},{"id":"126","full_name":"Karl, Holger","first_name":"Holger","last_name":"Karl"},{"full_name":"Shi, Ling","last_name":"Shi","first_name":"Ling"}],"publication_identifier":{"issn":["0005-1098"]},"title":"Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems","year":"2019","publication_status":"published","date_updated":"2022-01-06T06:52:32Z","language":[{"iso":"eng"}],"article_number":"108759","doi":"10.1016/j.automatica.2019.108759"},{"citation":{"chicago":"Leong, Alex S., Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl, and Ling Shi. “Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber–Physical Systems.” <i>Automatica</i> 113 (2019). <a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">https://doi.org/10.1016/j.automatica.2019.108759</a>.","short":"A.S. Leong, A. Ramaswamy, D.E. Quevedo, H. Karl, L. Shi, Automatica 113 (2019).","apa":"Leong, A. S., Ramaswamy, A., Quevedo, D. E., Karl, H., &#38; Shi, L. (2019). Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems. <i>Automatica</i>, <i>113</i>, Article 108759. <a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">https://doi.org/10.1016/j.automatica.2019.108759</a>","ieee":"A. S. Leong, A. Ramaswamy, D. E. Quevedo, H. Karl, and L. Shi, “Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems,” <i>Automatica</i>, vol. 113, Art. no. 108759, 2019, doi: <a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">10.1016/j.automatica.2019.108759</a>.","ama":"Leong AS, Ramaswamy A, Quevedo DE, Karl H, Shi L. Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems. <i>Automatica</i>. 2019;113. doi:<a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">10.1016/j.automatica.2019.108759</a>","bibtex":"@article{Leong_Ramaswamy_Quevedo_Karl_Shi_2019, title={Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems}, volume={113}, DOI={<a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">10.1016/j.automatica.2019.108759</a>}, number={108759}, journal={Automatica}, publisher={Elsevier BV}, author={Leong, Alex S. and Ramaswamy, Arunselvan and Quevedo, Daniel E. and Karl, Holger and Shi, Ling}, year={2019} }","mla":"Leong, Alex S., et al. “Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber–Physical Systems.” <i>Automatica</i>, vol. 113, 108759, Elsevier BV, 2019, doi:<a href=\"https://doi.org/10.1016/j.automatica.2019.108759\">10.1016/j.automatica.2019.108759</a>."},"volume":113,"user_id":"158","_id":"35583","publisher":"Elsevier BV","status":"public","department":[{"_id":"57"}],"keyword":["Electrical and Electronic Engineering","Control and Systems Engineering"],"type":"journal_article","date_created":"2023-01-09T16:44:58Z","publication":"Automatica","doi":"10.1016/j.automatica.2019.108759","language":[{"iso":"eng"}],"article_number":"108759","intvolume":"       113","publication_status":"published","date_updated":"2023-01-09T16:45:15Z","publication_identifier":{"issn":["0005-1098"]},"author":[{"first_name":"Alex S.","last_name":"Leong","full_name":"Leong, Alex S."},{"full_name":"Ramaswamy, Arunselvan","first_name":"Arunselvan","last_name":"Ramaswamy"},{"first_name":"Daniel E.","last_name":"Quevedo","full_name":"Quevedo, Daniel E."},{"full_name":"Karl, Holger","last_name":"Karl","first_name":"Holger"},{"first_name":"Ling","last_name":"Shi","full_name":"Shi, Ling"}],"year":"2019","title":"Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems"},{"language":[{"iso":"eng"}],"article_number":"108680","doi":"10.1016/j.automatica.2019.108680","publication_identifier":{"issn":["0005-1098"]},"author":[{"full_name":"Ding, Kemi","first_name":"Kemi","last_name":"Ding"},{"full_name":"Ren, Xiaoqiang","first_name":"Xiaoqiang","last_name":"Ren"},{"full_name":"Quevedo, Daniel E.","last_name":"Quevedo","first_name":"Daniel E."},{"first_name":"Subhrakanti","last_name":"Dey","full_name":"Dey, Subhrakanti"},{"full_name":"Shi, Ling","first_name":"Ling","last_name":"Shi"}],"year":"2019","title":"Defensive deception against reactive jamming attacks in remote state estimation","intvolume":"       113","date_updated":"2023-01-09T16:45:59Z","publication_status":"published","date_created":"2023-01-09T16:45:46Z","department":[{"_id":"57"}],"keyword":["Electrical and Electronic Engineering","Control and Systems Engineering"],"type":"journal_article","publication":"Automatica","_id":"35584","publisher":"Elsevier BV","volume":113,"user_id":"158","status":"public","citation":{"ama":"Ding K, Ren X, Quevedo DE, Dey S, Shi L. Defensive deception against reactive jamming attacks in remote state estimation. <i>Automatica</i>. 2019;113. doi:<a href=\"https://doi.org/10.1016/j.automatica.2019.108680\">10.1016/j.automatica.2019.108680</a>","bibtex":"@article{Ding_Ren_Quevedo_Dey_Shi_2019, title={Defensive deception against reactive jamming attacks in remote state estimation}, volume={113}, DOI={<a href=\"https://doi.org/10.1016/j.automatica.2019.108680\">10.1016/j.automatica.2019.108680</a>}, number={108680}, journal={Automatica}, publisher={Elsevier BV}, author={Ding, Kemi and Ren, Xiaoqiang and Quevedo, Daniel E. and Dey, Subhrakanti and Shi, Ling}, year={2019} }","mla":"Ding, Kemi, et al. “Defensive Deception against Reactive Jamming Attacks in Remote State Estimation.” <i>Automatica</i>, vol. 113, 108680, Elsevier BV, 2019, doi:<a href=\"https://doi.org/10.1016/j.automatica.2019.108680\">10.1016/j.automatica.2019.108680</a>.","short":"K. Ding, X. Ren, D.E. Quevedo, S. Dey, L. Shi, Automatica 113 (2019).","chicago":"Ding, Kemi, Xiaoqiang Ren, Daniel E. Quevedo, Subhrakanti Dey, and Ling Shi. “Defensive Deception against Reactive Jamming Attacks in Remote State Estimation.” <i>Automatica</i> 113 (2019). <a href=\"https://doi.org/10.1016/j.automatica.2019.108680\">https://doi.org/10.1016/j.automatica.2019.108680</a>.","apa":"Ding, K., Ren, X., Quevedo, D. E., Dey, S., &#38; Shi, L. (2019). Defensive deception against reactive jamming attacks in remote state estimation. <i>Automatica</i>, <i>113</i>, Article 108680. <a href=\"https://doi.org/10.1016/j.automatica.2019.108680\">https://doi.org/10.1016/j.automatica.2019.108680</a>","ieee":"K. Ding, X. Ren, D. E. Quevedo, S. Dey, and L. Shi, “Defensive deception against reactive jamming attacks in remote state estimation,” <i>Automatica</i>, vol. 113, Art. no. 108680, 2019, doi: <a href=\"https://doi.org/10.1016/j.automatica.2019.108680\">10.1016/j.automatica.2019.108680</a>."}},{"user_id":"238","volume":67,"page":"194–207","language":[{"iso":"eng"}],"_id":"42220","date_updated":"2023-02-17T14:38:38Z","intvolume":"        67","year":"2019","title":"Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach","status":"public","author":[{"full_name":"Guo, Z.","last_name":"Guo","first_name":"Z."},{"full_name":"Shi, D.","first_name":"D.","last_name":"Shi"},{"full_name":"Quevedo, D. E.","first_name":"D. E.","last_name":"Quevedo"},{"first_name":"L.","last_name":"Shi","full_name":"Shi, L."}],"type":"journal_article","department":[{"_id":"57"}],"date_created":"2023-02-17T14:34:53Z","publication":"Trans. Signal Processing","issue":"1","citation":{"ieee":"Z. Guo, D. Shi, D. E. Quevedo, and L. Shi, “Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach,” <i>Trans. Signal Processing</i>, vol. 67, no. 1, pp. 194–207, 2019.","apa":"Guo, Z., Shi, D., Quevedo, D. E., &#38; Shi, L. (2019). Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach. <i>Trans. Signal Processing</i>, <i>67</i>(1), 194–207.","short":"Z. Guo, D. Shi, D.E. Quevedo, L. Shi, Trans. Signal Processing 67 (2019) 194–207.","chicago":"Guo, Z., D. Shi, D. E. Quevedo, and L. Shi. “Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach.” <i>Trans. Signal Processing</i> 67, no. 1 (2019): 194–207.","mla":"Guo, Z., et al. “Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach.” <i>Trans. Signal Processing</i>, vol. 67, no. 1, 2019, pp. 194–207.","bibtex":"@article{Guo_Shi_Quevedo_Shi_2019, title={Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach}, volume={67}, number={1}, journal={Trans. Signal Processing}, author={Guo, Z. and Shi, D. and Quevedo, D. E. and Shi, L.}, year={2019}, pages={194–207} }","ama":"Guo Z, Shi D, Quevedo DE, Shi L. Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach Secure State Estimation Against Integrity Attacks: A Gaussian Mixture Model Approach. <i>Trans Signal Processing</i>. 2019;67(1):194–207."}}]