Interdependence design principles in practice - Vignati, Micael; Johnson, Matthew; Bunch, Larry; Carff, John; Duran, Daniel (Frontiers in Physics, 2022)
Adaptability lies at the heart of effective teams and it is through management of interdependence that teams are able to adapt. This makes interdependence a critical factor of human-machine teams. In spite of this, engineers building human-machine systems still rely on the same tools and techniques used to build individual behaviors which were never designed to address the complexity that stems from interdependence. Many engineering approaches lack any systematic or formal method for identifying interdependence, which forces ad hoc solutions or workarounds, leaving engineers blind to the issues and consequences of failing to adequately address interdependence within human-machine teams. While some work has been done on identifying, characterizing and categorizing interdependence, structures that enable human-machine systems to actively manage and exploit interdependence are currently ad hoc and lack theoretical and systematic rigor. This gap between theories of interdependence and operable tooling leaves engineers either unaware of interdependence or unequipped to build solutions to manage it. In previous work we proposed ways to identify interdependence through analysis and a framework for understanding the different aspects of interdependence involved in teamwork. Here we take the next step to operationalize these concepts. We describe a formalized structure, the Joint Activity Graph (JAG), built on interdependence design principles to capture the essence of joint activity and to support intelligent management of interdependence during execution. This structure is consistent with the “4S interdependence framework for understanding teamwork”, and integrated with “Interdependence Analysis” to support design and execution of joint activity. To demonstrate the effectiveness of such a structure at supporting adaptability through the management of interdependence, we use the capture-the-flag domain with heterogeneous teams of unmanned aerial vehicles and unmanned ground systems. In this dynamic adversarial domain, we show how agents can make use of the information provided by JAG to generally and pragmatically react and adapt to perturbations in the joint activity, the environment, or the team and explicitly manage and exploit interdependence to produce effective teamwork. In doing so,we demonstrate how flexible and adaptive teamwork can be achieved through formally guided design that supports effective management of interdependence.