Research / Themes / Innovation / Agent-based modeling
Opportunity theories of crime have highlighted the benefits of a shift in focus from the criminal motivation of people to the contexts in which crime events occur. However, testing of these theories has been handicapped by a lack of micro-level data and modeling tools that can capture the dynamic interactions of individuals and the context in which they occur. This research explores a new methodology for testing theory that draws upon extant theory and empirical research to develop individually-based simulation models. Three versions of a street robbery model are created based on routine activity theory and empirical research and implemented in Agent Analyst software. Each version adds a degree of complexity to the basic model (i.e., first temporal and then spatio-temporal constraints).
E.R. Groff. (In press). Agent-based Modeling for Understanding Space-time Patterns of Crime. In H. Bruinsma and D. Weisburd (eds), Encyclopedia of Criminology and Criminal Justice. Springer: New York, NY.
Groff, E.R. and M.J. Fraley. Moving Agents on Representative Networks. In K. Johnston (ed), Agent Analyst: Agent-Based Modeling in ArcGIS. ESRI Press: Redlands, CA. 2012. Pp. 203-238. http://resources.arcgis.com/en/help/agent-analyst/. (Peer Reviewed).
Groff, E.R. and M.J. Fraley. Adding Complexity to Agent Movement on Representative Networks. In K. Johnston, et al (ed), Agent Analyst: Agent-Based Modeling in ArcGIS. ESRI Press: Redlands, CA. 2012. Pp. 359-410. http://resources.arcgis.com/en/help/agent-analyst/. (Peer Reviewed).
Groff, E. R. and L. Mazzerole. Simulated Experiments and their Potential Role in Criminology and Criminal Justice. Journal of Experimental Criminology, 4(3). 2008.