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We present an experimentation platform for coalition situationalunderstanding research that highlights capabilities in explainable artificialintelligence/machine learning (AI/ML) and integration of symbolic andsubsymbolic AI/ML approaches for event processing. The SituationalUnderstanding Explorer (SUE) platform is designed to be lightweight, to easilyfacilitate experiments and demonstrations, and open. We discuss ourrequirements to support coalition multi-domain operations with emphasis onasset interoperability and ad hoc human-machine teaming in a dense urbanterrain setting. We describe the interface functionality and give examples ofSUE applied to coalition situational understanding tasks.

An Experimentation Platform for Explainable Coalition Situational Understanding