Uncertainty, Stress and Decision Simulation
Abstract
In May 2000, Micro Analysis and Design, Inc. and Klein Associates, Inc., were awarded a Phase 1 SBIR to research and develop computational models of decision making in stressful and uncertain conditions (Topic #N00-074, Modeling and Simulation of Decision-making Under Uncertainty). This research was motivated by the need for improved behavioral realisms in computer generated forces (CGFs) with an eye toward reducing and, perhaps, even eliminating the need for human-in-the-loop simulations. Rather than continue in the tradition of rational choice theories and rule-based expert systems, we took a novel approach to this research and began work on a model of Recognition Primed Decision making (RPD). The RPD model explains how people can use their experience to arrive at good decisions without having to compare the strengths and weaknesses of alternative courses of action. For this reason, RPD theory seems to be a natural foundation for a more realistic model of human decision making under stress and uncertainty, but it also presents novel challenges from a computational point of view. We summarize below how we addressed these challenges during our Phase 1 work, and how we will work toward a validated modeling technology under a Phase 2 contract.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 26, 2000
- Accession Number
- ADA383543
Entities
People
- Patricia Mcdermott
- Stacey Mcilwaine
- Walter Warwick