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An Agent-Based Model of Burglary

Author

Listed:
  • Nick Malleson
  • Andrew Evans
  • Tony Jenkins

    (School of Computing, University of Leeds, Leeds LS2 9JT, England)

Abstract

Occurrences of crime are complex phenomena. They are the result of a large number of interrelated elements which can include environmental factors as well as complex human behaviours. Traditionally, crime occurrences have been modelled using statistical techniques, and although such approaches are useful, they face difficulties in providing predictive analyses and with the integration of behavioural information. Also, it is particularly difficult to account for the strongly influential effect of local urban form. Agent-based modelling is a relatively new modelling paradigm that has generated a considerable amount of interest. An agent is an independent component of a system which interacts with other agents and its environment to achieve goals. In this manner, large systems of agents can be created to mimic real scenarios. Most importantly, the agents can incorporate behavioural information to determine how they should achieve their goals, and models can include a highly detailed environment. This paper presents an agent-based model used to predict burglary rates, which, despite its simplicity, yields interesting results. We apply the model to the city of Leeds, UK. The model indicates that the urban configuration in Leeds is a major element in determining the level of crime across the city. It also demonstrates that agent-based modelling is an excellent tool for these types of analyses with much potential.

Suggested Citation

  • Nick Malleson & Andrew Evans & Tony Jenkins, 2009. "An Agent-Based Model of Burglary," Environment and Planning B, , vol. 36(6), pages 1103-1123, December.
    • Handle: RePEc:sae:envirb:v:36:y:2009:i:6:p:1103-1123
    DOI: 10.1068/b35071
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    References listed on IDEAS

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    1. Michael Batty, 2005. "Agents, Cells, and Cities: New Representational Models for Simulating Multiscale Urban Dynamics," Environment and Planning A, , vol. 37(8), pages 1373-1394, August.
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