An Application of Explainable Multi-Agent Reinforcement Learning for Spectrum Situational Awareness
dc.contributor.author | Perini, Dominick J. | en |
dc.contributor.author | Muller, Braeden P. | en |
dc.contributor.author | Kopacz, Justin | en |
dc.contributor.author | Michaels, Alan J. | en |
dc.date.accessioned | 2025-04-28T17:18:05Z | en |
dc.date.available | 2025-04-28T17:18:05Z | en |
dc.date.issued | 2025-04-10 | en |
dc.date.updated | 2025-04-25T13:46:31Z | en |
dc.description.abstract | Allocating low-bandwidth radios to observe a wide portion of a spectrum is a key class of search-optimization problems that requires system designers to leverage limited resources and information efficiently. This work describes a multi-agent reinforcement learning system that achieves a balance between tuning radios to newly observed energy while maintaining regular sweep intervals to yield detailed captures of both short- and long-duration signals. This algorithm, which we have named SmartScan, and system implementation have demonstrated live adaptations to dynamic spectrum activity, persistence of desirable sweep intervals, and long-term stability. The SmartScan algorithm was also designed to fit into a real-time system by guaranteeing a constant inference latency. The result is an explainable, customizable, and modular approach to implementing intelligent policies into the scan scheduling of a spectrum monitoring system. | en |
dc.description.version | Published version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Perini, D.J.; Muller, B.P.; Kopacz, J.; Michaels, A.J. An Application of Explainable Multi-Agent Reinforcement Learning for Spectrum Situational Awareness. Electronics 2025, 14, 1533. | en |
dc.identifier.doi | https://doi.org/10.3390/electronics14081533 | en |
dc.identifier.uri | https://hdl.handle.net/10919/126246 | en |
dc.language.iso | en | en |
dc.publisher | MDPI | en |
dc.rights | Creative Commons Attribution 4.0 International | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
dc.title | An Application of Explainable Multi-Agent Reinforcement Learning for Spectrum Situational Awareness | en |
dc.title.serial | Electronics | en |
dc.type | Article - Refereed | en |
dc.type.dcmitype | Text | en |