Abstract by Levi Pike
Multi-Human Management of a Hub-Based Colony: Efficiency and Robustness in the Cooperative Best-M-of-N Task
Swarm robotics is an emerging field that is expected to provide robust solutions to spatially distributed problems. Human operators will often be required to guide a swarm in the fulfillment of a mission. Occasionally, large tasks may require multiple spatial swarms to cooperate in their completion. We hypothesize that when latency, bandwidth, operator dropout, and communication noise are significant factors, human organizations that promote individual initiative perform more effectively and resiliently than hierarchies in the cooperative best-m-of-n task. Simulations automating the behavior of hub-based swarm agents and groups of human operators will be used to evaluate this hypothesis. To make the comparisons between the team and hierarchies meaningful, we propose exploring parameter values determining how simulated human operators behave in teams and hierarchies to optimize the performance of the respective organizations.