Christopher, LaurenBoler, WilliamWieczorek, CalvinCrespo, JonahWitcher, PaulHawkins, Scot A.Stewart, James2017-10-192017-10-192016-10Christopher, 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.2016.7780277https://hdl.handle.net/1805/14332PSO 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.enPublisher Policyhuman in the swarmblended intelligencepheromonesConference proceedings