A Neuro-inspired Theory of Joint Human-Swarm Interaction
Jonas D. Hasbach, Maren Bennewitz

TL;DR
This paper introduces a neuro-inspired joint systems theory for human-swarm interaction, aiming to enhance the adaptability, robustness, and scalability of human-swarm systems by informing their design through cognitive systems engineering principles.
Contribution
It presents a novel neuro-inspired theoretical framework for human-swarm interaction, integrating cognitive systems engineering to predict and improve HSI dynamics.
Findings
Provides a new theoretical model for HSI
Predicts adaptive and scalable HSI behaviors
Informs design of human-swarm interfaces
Abstract
Human-swarm interaction (HSI) is an active research challenge in the realms of swarm robotics and human-factors engineering. Here we apply a cognitive systems engineering perspective and introduce a neuro-inspired joint systems theory of HSI. The mindset defines predictions for adaptive, robust and scalable HSI dynamics and therefore has the potential to inform human-swarm loop design.
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Taxonomy
TopicsRobot Manipulation and Learning · Reinforcement Learning in Robotics · Cognitive Science and Mapping
