Crime reduction through simulation: An agent-based model of burglary

Traditionally, researchers have employed statistical methods to model crime. However, these approaches are limited by being unable to model individual actions and behaviour. Brantingham and Brantingham (1993) described that in their opinion a useful and productive model for simulating crime would have the ability to model the occurrence of crime and the motivations behind it both temporally and spatially. This paper presents the construction and application of an agent-based model (ABM) for simulating occurrences of residential burglary at an individual level. It presents a novel framework that allows both human and environmental factors to be simulated. Although other agent-based models of crime do exist, this research represents the first working example of integrating a behavioural framework into an ABM for the simulation of crime. An artificial city, loosely based on the real city of Leeds, UK, and an artificial population were constructed, and experiments were run to explore the potential of the model to realistically simulate the main processes and drivers within this system. The results are highly promising, demonstrating the potential of this approach for both understanding processes behind crime and improving policies and developing effective crime prevention strategies.