The search for invariants is a fundamental aim of scientific endeavors. These invariants, such as Newton's laws of motion, allow us to model and predict the behavior of systems across many different problems. In the nascent field of Human-Swarm Interaction (HSI), a systematic identification of fundamental invariants is still lacking. Discovering and formalizing these invariants will provide a foundation for developing, and better understanding, effective methods for HSI. We propose two invariants underlying HSI for geometric-based swarms: (1) collective state is the fundamental percept associated with a bio-inspired swarm, and (2) a human's ability to influence and understand the collective state of a swarm is determined by the balance between the span and persistence. We provide evidence of these invariants by synthesizing much of our previous work in the area of HSI with several new results, including a novel user study where users manage multiple swarms simultaneously. We also discuss how these invariants can be applied to enable more efficient and successful teaming between humans and bio-inspired collectives and identify several promising directions for future research into the invariants of HSI.

Stimulus-driven orienting of attention toward a novel, salient stimulus is a highly adaptive behavior. In an opposing vein, it is also crucial to endogenously redirect attention to other stimuli of behavioral significance if the attended stimulus was evaluated to be unimportant. This stimulus-driven orienting and subsequent reorienting of attention are known to be mediated by similar neural substrates. However, this might be because reorienting was triggered by a sensory transition exogenously capturing attention, such as an abrupt onset of a new stimulus. Here, we used fMRI to measure the human brain’s activity when attention captured by a salient distractor is endogenously reoriented toward the concurrent main task, without any exogenous shifting of attention. As results, the transient activity of the anterior insula (AI) signaled such endogenous reorienting, predicting behavioral performance. This finding points to the central role of the AI in purely endogenous, self-regulatory control of attention.

Abstract-Human-swarm interaction methods often allow a human to influence a swarm through either leadership or predation. These methods of influence have two main limitations:(1) although leaders sustain influence over nominal agents for a long period of time, they tend to cause all collective structures to turn in to flocks (negating the benefit of other swarm formations) and (2) predators tend to cause collective structures to fragment. We introduce the use of mediators as a novel shared control method for human-swarm influence and use mediators to shape Couzin-like tori [1]. The mediator method uses special agents that operate from within the spatial center of a swarm. This approach allows a human operator to transform and move a dynamic torus formation while sustaining influence over the torus, avoiding fragmentation, and maintaining the torus' connectivity. The use of mediators allows a human to mold and adapt the torus' behavior and structure to a wide range of spatio-temporal tasks such as military protection and decontamination tasks.

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