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.

这篇研究论文介绍了一个名为 SUE 的实验平台，它能集成符号 AI/ML 和子符号 AI/ML 方法进行事件处理，以及支持跨领域作战，强调资产互操作性和人机团队协同，尤其适用于密集城市地形的联合态势理解任务。