SBIR-STTR Award

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.

Keywords:
Decision-Making Decision Emergency Crisis Chaotic Environment Data-Poor Environment Recognition-Primed Neural-Networking

Crisis decision-making is difficult and error-prone because it involves time-urgency, physical and emotional stress, chaotic conditions, and poor data availability/quality. This SBIR project will investigate, develop, and deploy a web-based software system (called PolARES) that supports key decisions for crisis management and battlefield applications. This system will produce a revolutionary improvement in decision performance for both experienced and novice decision makers. Successful crisis decision-making employs a psychology termed recognition-primed decision-making, a method that uses limited event observations to force quick recognition of an analogous scenario from a knowledge base. The PolARES decision system will support rapid decision-making in battlefield, emergency, and disaster situations. PolARES will include an extensive relational database of decision scenarios: event/decision pairs tailored to a target decision maker and decision space. PolARES will employ an advanced artificial intelligence algorithm to lead the decision maker through a limited set of questions to a rapid choice of a stored scenario. The tool will then adapt the base scenario to actual event conditions. A feasibility prototype demonstrated PolARES’ potential for chemical emergency response in Phase I of this SBIR. In Phase 2, PolARES will be applied to tactical military decision-making and other crisis decision environments.

Keywords:
Decision-Making, Emergency, Crisis, Chaotic Environment, Data-Poor Environment, Recognition-Primed, Neural Networking, Artificial Intelligence