Semi-Supervised Learning for Assessing Team Simulations, or SLATS, will enable commanders, staff, and support personnel to plan, prepare, execute, and assess collective training events within the Synthetic Training Environment (STE). Semi-supervised learning is a machine learning technique that leverages small amounts of manually labeled data to make sense of patterns in unlabeled data which is generally available in larger quantities. Semi-supervised learning incorporated into the SLATS system will be used to assess team quality. Instructors will be provided actionable insights such as overall analysis, common errors and tasks that require additional training.
