Elaine M. Raybourn
The present paper outlines an approach to representing cognitive, cultural, and physiological variability in the computational representation an individual U.S. peacekeeper as he interacts with an unexpected target (two young Iraqi girls) in an ambiguous situation while faced with a high-consequence decision that will greatly impact subsequent events. This project sought to demonstrate steps toward a realistic computational representation of the variability encountered in individual human behavior. Realism, as conceptualized in this project, required that the human representation address the underlying psychological, cultural, physiological, and environmental stressors. A software model of a peacekeeping scenario adapted from a Desert Storm incident was developed in which the framework consisted of a computational instantiation of Recognition Primed Decision Making in the context of a Naturalistic Decision Making model (Klein, 1997). Recognition Primed Decision Making was augmented with an underlying foundation based on an understanding of human neurophysiology and it’s relationship to human cognitive processes. The goal was to provide initial steps toward a computational representation of human variability in cultural, cognitive, and physiological (arousal, emotions, etc.) state order to attain a better understanding of the full depth of human decision-making processes in the context of ambiguity, novelty, and heightened arousal.