An Experimentation Platform for Explainable Coalition Situational
  Understanding
  We present an experimentation platform for coalition situational
understanding research that highlights capabilities in explainable artificial
intelligence/machine learning (AI/ML) and integration of symbolic and
subsymbolic AI/ML approaches for event processing. The Situational
Understanding Explorer (SUE) platform is designed to be lightweight, to easily
facilitate experiments and demonstrations, and open. We discuss our
requirements to support coalition multi-domain operations with emphasis on
asset interoperability and ad hoc human-machine teaming in a dense urban
terrain setting. We describe the interface functionality and give examples of
SUE applied to coalition situational understanding tasks.
