Shared Versus Centralized Leadership on Task Allocation Decisions in Multiagent Systems

Multiagent systems deployed in dynamic environments depend on timely and accurate task allocation between human operators and autonomous agents. Current approaches predominantly assign leadership authority to a single agent, either a human supervisor or an automated arbitrator, leaving out examination of shared leadership. This study compared shared and centralized leadership in a simulated search-and-rescue task in which 46 participants coordinated with one autonomous agent and four unmanned aerial vehicles (UAVs) to detect and classify objects. Under centralized leadership, participants held unilateral authority over task allocation. Under shared leadership, authority was negotiated each trial through a claiming-granting mechanism. Results showed that shared leadership produced significantly higher performance than centralized leadership. Analysis of UAV assignment revealed that perceived competence predicted allocation across both structures, while trust was significant only under shared leadership. These findings demonstrate that shared authority yields measurable performance advantages and engages reliance mechanisms differently than fixed-authority.