Human-automated planner collaboration in complex resource allocation decision support systems

Abstract

In resource allocation problems for systems with moving planning horizons and significant uncertainty, typical of supervisory control environments, it is critical that some balance of human-automated planning collaboration be achieved. These systems typically require leveraging the computational power of automation, as well as the experience and judgment of human decision makers. Humans and automated planners can interact through degrees of collaboration from automation-directed to human-directed, and such collaboration is inherently distinct from previously discussed levels of automation. In the context of a command and control mission planning task, we show that across a number of metrics, there is no clear dominant human-automated planner collaboration scheme for resource allocation problems using three distinct instantiations of human-automated planner collaboration. Rather, the ultimate selection for the best resource allocation decision support system will depend on a cost-benefit approach that could include mitigation of workload, conformance to intended design characteristics, as well as the need to maximize overall mission performance.