Combining modeling and gaming for predictive analytics
Pacific Northwest National Laboratory, Richland, WA, USA
Security Informatics 2012, 1:11 doi:10.1186/2190-8532-1-11Published: 22 August 2012
Our most significant security challenges involve people. While human behavior has long been studied, computational modeling of human behavior is early in its development. An inherent challenge in modeling of human behavior is efficient and accurate transfer of knowledge from humans to models, and subsequent retrieval. The simulated real-world environments of games present one avenue for knowledge generation and transfer. In this paper we describe our approach of combining modeling and gaming disciplines to develop predictive capabilities, using formal models to inform game development, and using games to provide data for modeling. We also describe the development of a prototype “Illicit Trafficking Game” that we used as a tool to exercise, evaluate and refine our approach. The resulting predictive capability combines human expertise and actions with computational modeling capabilities, resulting in a predictive capability that may approach the richness and diversity of human behaviors we wish to predict.