Adaptive Recognition-Primed Emergency Support (ARES) System

Crisis decision-making is difficult and error-prone because it usually involves high time-urgency, physical and emotional stress, chaotic conditions and poor data availability / quality. This SBIR project will investigate, develop and employ a hardware/software system to support key crisis decisions for crisis management and battlefield applications. This system will produce a revolutionary improvement in decision performance for experienced and novice decision-makers. Successful crisis decision-making employs a psychology termed “recognition-primed decision-making,” a method that uses event observations to force quick recognition of an analog scenario from a knowledge base. The Adaptive Recognition-primed Emergency Support System (ARES) will support rapid decision-making in operational emergency and battlefield use. The core of ARES will be an extensive relational database of decision scenarios – event / decision pairs tailored to a target decision-maker and decision set. Emulating the recognition-primed decision process, the capability will employ an advanced neural-networking algorithm to “walk” the decision-maker through a limited set of questions to a rapid choice of a scenario. The tool will then adapt the base scenario to actual event conditions, “tuning” the decisions for the specific event. ARES will be demonstrated for CBRNE emergency response, then expanded to battlefield and other crisis decision environments.