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Visualization Tools for Prescriptive Analysis of a Complex Adaptive System Model of Pilot Retention

Abstract This paper discusses a prototype agent-based simulation for examining United States Air Force pilot retention issues. The United States Air Force expends significant time and resources training pilots and thus wants to retain these trained pilots. Analysts use models to examine potential solutions to the retention problem. However, these models fail to capture the human aspects of the problem. Complex adaptive system (CAS) models provide a means to model the human aspects of complex decisions and problems. We describe the pilot inventory complex adaptive system (PICAS) model, a proof-of-concept CAS simulation wherein pilots are modelled as agents whose behaviours are influenced by key environmental and internal considerations. Although they seem promising as a means of increasing the accuracy of human-behaviour-based modelling,CAS models require extending current analytical paradigms by explicitly incorporating techniques for visualizing model output. In this paper, we describe the use of three interdependent visualization techniques for improving model analyses and demonstrate the use of these techniques using the prototype PICAS model.