RED EMERGENCE: Ontology-driven algorithmic research for Russian Brigade Tactical Group operations.
RED EMERGENCE is designed to provide an advanced AI model that can serve as a “highly competent adversary” when paired against a human BLUFOR opponent.
RED EMERGENCE provides an innovative way to enhance the capability of both OPFOR and BLUFOR wargame participants by providing a platform that will complement their own operational abilities. RED EMERGENCE utilizes natural language processing (NLP) to extract emergent doctrinal ideas from both OPFOR and BLUFOR publications, and then uses an “artificial entity” for evaluating those doctrinal ideas.
RED EMERGENCE works much the same way that ALPHA GO used reinforcement learning and game replay to defeat a master-level human opponent, but without the excessive computational burden needed for ALPHA GO.
