{"file":[{"date_updated":"2019-09-23T16:21:16Z","file_name":"ifacconf.pdf","file_id":"13444","content_type":"application/pdf","access_level":"local","date_created":"2019-09-23T15:48:33Z","creator":"aredder","relation":"main_file","file_size":371429}],"date_updated":"2022-01-06T06:51:36Z","title":"Deep reinforcement learning for scheduling in large-scale networked control systems","conference":{"start_date":"2019-09-16","location":"Chicago, USA","name":"8th IFAC Workshop on Distributed Estimation and Control in Networked Systems - NECSYS 2019","end_date":"2019-09-17"},"abstract":[{"lang":"eng","text":"This work considers the problem of control and resource allocation in networked\r\nsystems. To this end, we present DIRA a Deep reinforcement learning based Iterative Resource\r\nAllocation algorithm, which is scalable and control-aware. Our algorithm is tailored towards\r\nlarge-scale problems where control and scheduling need to act jointly to optimize performance.\r\nDIRA can be used to schedule general time-domain optimization based controllers. In the present\r\nwork, we focus on control designs based on suitably adapted linear quadratic regulators. We\r\napply our algorithm to networked systems with correlated fading communication channels. Our\r\nsimulations show that DIRA scales well to large scheduling problems."}],"date_created":"2019-09-23T16:00:58Z","publication_status":"published","file_date_updated":"2019-09-23T16:21:16Z","author":[{"orcid":"https://orcid.org/0000-0001-7391-4688","full_name":"Redder, Adrian","last_name":"Redder","id":"52265","first_name":"Adrian"},{"id":"66937","first_name":"Arunselvan","full_name":"Ramaswamy, Arunselvan","last_name":"Ramaswamy","orcid":"https://orcid.org/ 0000-0001-7547-8111"},{"last_name":"Quevedo","full_name":"Quevedo, Daniel","first_name":"Daniel"}],"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1905.05992"}],"project":[{"_id":"52","name":"Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"has_accepted_license":"1","language":[{"iso":"eng"}],"publication":"Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems","_id":"13443","status":"public","year":"2019","user_id":"52265","keyword":["Networked control systems","deep reinforcement learning","large-scale systems","resource scheduling","stochastic control"],"type":"conference","oa":"1","citation":{"chicago":"Redder, Adrian, Arunselvan Ramaswamy, and Daniel Quevedo. “Deep Reinforcement Learning for Scheduling in Large-Scale Networked Control Systems.” In <i>Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems</i>, 2019.","mla":"Redder, Adrian, et al. “Deep Reinforcement Learning for Scheduling in Large-Scale Networked Control Systems.” <i>Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems</i>, 2019.","apa":"Redder, A., Ramaswamy, A., &#38; Quevedo, D. (2019). Deep reinforcement learning for scheduling in large-scale networked control systems. In <i>Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems</i>. Chicago, USA.","short":"A. Redder, A. Ramaswamy, D. Quevedo, in: Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, 2019.","ama":"Redder A, Ramaswamy A, Quevedo D. Deep reinforcement learning for scheduling in large-scale networked control systems. In: <i>Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems</i>. ; 2019.","ieee":"A. Redder, A. Ramaswamy, and D. Quevedo, “Deep reinforcement learning for scheduling in large-scale networked control systems,” in <i>Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems</i>, Chicago, USA, 2019.","bibtex":"@inproceedings{Redder_Ramaswamy_Quevedo_2019, title={Deep reinforcement learning for scheduling in large-scale networked control systems}, booktitle={Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems}, author={Redder, Adrian and Ramaswamy, Arunselvan and Quevedo, Daniel}, year={2019} }"},"ddc":["620"]}