Asset Allocation with Swarm/Human Blended Intelligence

dc.contributor.authorChristopher, Lauren
dc.contributor.authorBoler, William
dc.contributor.authorWieczorek, Calvin
dc.contributor.authorCrespo, Jonah
dc.contributor.authorWitcher, Paul
dc.contributor.authorHawkins, Scot A.
dc.contributor.authorStewart, James
dc.contributor.departmentDepartment of Electrical and Computer Engineering, School of Engineering and Technologyen_US
dc.date.accessioned2017-10-19T15:47:05Z
dc.date.available2017-10-19T15:47:05Z
dc.date.issued2016-10
dc.description.abstractPSO has been used to demonstrate the near-real-time optimization of frequency allocations and spatial positions for receiver assets in highly complex Electronic Warfare (EW) environments. The PSO algorithm computes optimal or near-optimal solutions so rapidly that multiple assets can be exploited in real-time and re-optimized on the fly as the situation changes. The allocation of assets in 3D space requires a blend of human intelligence and computational optimization. This paper advances the research on the tough problem of how humans interface to the swarm for directing the solution. The human intelligence places new pheromone-inspired spheres of influence to direct the final solution. The swarm can then react to the new input from the human intelligence. Our results indicate that this method can maintain the speed goal of less than 1 second, even with multiple spheres of pheromone influence in the solution space.en_US
dc.eprint.versionAuthor's manuscripten_US
dc.identifier.citationChristopher, L., Boler, W., Wieczorek, C., Crespo, J., Witcher, P., Hawkins, S. A., & Stewart, J. (2016, October). Asset allocation with swarm/human blended intelligence. In Swarm/Human Blended Intelligence Workshop (SHBI), 2016 (pp. 1-5). IEEE. https://doi.org/10.1109/SHBI.2016.7780277en_US
dc.identifier.urihttps://hdl.handle.net/1805/14332
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/SHBI.2016.7780277en_US
dc.relation.journalSwarm/Human Blended Intelligence Workshopen_US
dc.rightsPublisher Policyen_US
dc.sourceAuthoren_US
dc.subjecthuman in the swarmen_US
dc.subjectblended intelligenceen_US
dc.subjectpheromonesen_US
dc.titleAsset Allocation with Swarm/Human Blended Intelligenceen_US
dc.typeConference proceedingsen_US
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