Space-based teaming requires coordination across human operators using old (e.g., existing communication networks) and new (e.g., AI and robotic teammates) digital technologies (DTs) across great distances. Hence, methods are needed to observe resilience across multiple layers of coordination comprising DT-enabled space missions. This presented study simulates high-stakes scenarios to measure constructs like relaxation time, information entropy, and average mutual information (AMI) to evaluate team responses to perturbations. Our study involved two scenarios: one with nominal communications among space entities and another introducing resilience through deliberate perturbations. Eight participants who were members of the research team, engaged in these simulations. Communication flow and vehicle controls and position were measured. Using layered dynamics, we measure dynamic resilience curves (comprising enaction, adaptation, and recovery components) across the system before, during, and after perturbations. We ran two engineering tests of our resilience metrics. Key findings indicate that measures differentiated between the resilient team with shorter relaxation times and more effective adaptation to perturbations, marked by distinct phases of enaction, adaptation, and recovery. The AMI metric was found to be a more sensitive measure of team influence and resilience than communication frequency. This study contributes to future research in two ways. First, the simulation environment and continuous signal capture allows for the observation of adaptations. Second, the adoption of operationism provides an innovative approach to observing resilience.
Keywords: Distributed space operations; Dynamical systems; Human-machine teaming; Resilience measurement; Team cognition; Team coordination.
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