Digital Twins for Cognitive Situation Awareness

Situation analysis (SAn) multi-dimensional modeling from machine situation assessment (SAs) rarely presents results that match user cognitive reasoning of situation awareness (SAw). However, new machine opportunities exist that can support situation analytics from high performance modeling to go beyond computer simulations. Two recent advances afford SAn that include (1) artificial intelligence methods such as deep learning (DL) and neurosymbolic architectures, and (2) digital engineering to include open architectures and digital twins. While deep learning and open architectures are common in the last decade, recent advances in neurosymbolic approaches are becoming popular to combine neuro (e.g., DL) with probabilistic symbolic reasoning for cognitive understanding. Likewise open architectures allow many digital models to be connected through digital twins. This article highlights the opportunities for digital twins to enhance cognitive situation analytics to support situation control, situation understanding, as well as situation forecasting of plausible futures.