| Abstract |
We present an experimentation platform for coalition situa- tional understanding research that highlights capabilities in explainable artificial intelligence/machine learning (AI/ML) and integration of symbolic and subsymbolic AI/ML ap- proaches for event processing. The Situational Understanding Explorer (SUE) platform is designed to be lightweight, to eas- ily 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. |