The routine activity theory of crime holds that crimes occur only when motivated offenders encounter suitable targets in the absence of effective security measures that would otherwise disrupt the crime. Routine activity theory thus urges a physical conception of crime events driven by how offenders, victims and security (e.g., police) move and how they mix. The UC Mathematical and Simulation Modeling of Crime (UC MaSC) project has developed large-scale agent-based models and corresponding reaction-diffusion partial differential equation models of residential burglary based on routine activity theory. Used in conjunction, the discrete simulations and PDE models provide a means of exploring the causal mechanisms of crime hotspot formation. Analysis and simulation also point to one possible explanation for the divergent outcomes seen in real-world experimental tests of hotspot policing. The nature of these models and their implications for computational design of policing strategies will be discussed.
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