Information Search and Decision Making in Computer-Based Wildfire Simulations

Abstract

Decision making in complex environments has been investigated in many domains, including medicine, aviation, business, and police operations. However, how incident commanders (ICs) make protective-action recommendations (PARs) to populations exposed to wildfire risks is underinvestigated. In this study we examined the effect of expertise on IC non-time-limited information search and decision making and how ICs update information during the evolution of complex, computer-simulated wildfire scenarios. The results indicate that higher expertise reduces the overall amount of information being searched for, without affecting the quality of PAR decisions. In addition, a statistical trend suggests that information updating during the progression of the scenario involves disproportionate less-static information versus dynamic information. Finally, ICs demonstrated a strong preference for evacuation recommendations over alternative recommendations, even when an evacuation may result in less optimal outcomes.