Requirements for Computational Approaches to Analyzing Resilience in Human-Machine Teams

Abstract

Human-machine teams (HMTs) in complex work domains need to be able to adapt to variable and uncertain work demands. Computational modeling and simulation can provide novel approaches to the evaluation of HMTs performing complex joint activities, affording large-scale, quantitative analysis of team characteristics (such as system architecture and governance protocols) and their effects on resilience. Drawing from literature in resilience engineering, human-automation interaction, and cognitive systems engineering, this paper provides a theoretical exploration of the use of computational modeling and simulation to analyze resilience in HMTs. Findings from literature are summarized in a set of requirements that highlight key aspects of resilience in HMTs that need to be accounted for in future modeling and evaluation efforts. These requirements include a need to model HMTs as joint cognitive systems, the need to account for the interdependent nature of activity, the temporal dynamics of work, and the need to support formative exploration and inquiry. We provide a brief overview of existing modeling and simulation approaches to evaluating HMTs and discuss further steps for operationalizing the identified requirements.