dc.contributor.author | Murad, Abdulmajid Abdullah Yahya | |
dc.contributor.author | Kraemer, Frank Alexander | |
dc.contributor.author | Bach, Kerstin | |
dc.contributor.author | Taylor, Gavin | |
dc.date.accessioned | 2019-08-19T08:44:03Z | |
dc.date.available | 2019-08-19T08:44:03Z | |
dc.date.created | 2019-06-20T11:51:22Z | |
dc.date.issued | 2019 | |
dc.identifier.isbn | 978-1-7281-2731-6 | |
dc.identifier.uri | http://hdl.handle.net/11250/2608932 | |
dc.description.abstract | Reinforcement learning (RL) is capable of managing wireless, energy-harvesting IoT nodes by solving the problem of autonomous management in non-stationary, resource-constrained settings. We show that the state-of-the-art policy-gradient approaches to RL are appropriate for the IoT domain and that they outperform previous approaches. Due to the ability to model continuous observation and action spaces, as well as improved function approximation capability, the new approaches are able to solve harder problems, permitting reward functions that are better aligned with the actual application goals. We show such a reward function and use policy-gradient approaches to learn capable policies, leading to behavior more appropriate for IoT nodes with less manual design effort, increasing the level of autonomy in IoT. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | nb_NO |
dc.relation.ispartof | 2019 IEEE 13th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) | |
dc.title | Autonomous Management of Energy-Harvesting IoT Nodes Using Deep Reinforcement Learning | nb_NO |
dc.type | Chapter | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.pagenumber | 43-51 | nb_NO |
dc.identifier.doi | 10.1109/SASO.2019.00015 | |
dc.identifier.cristin | 1706390 | |
dc.description.localcode | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | nb_NO |
cristin.unitcode | 194,63,30,0 | |
cristin.unitcode | 194,63,10,0 | |
cristin.unitname | Institutt for informasjonssikkerhet og kommunikasjonsteknologi | |
cristin.unitname | Institutt for datateknologi og informatikk | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |