Optimising an agent-based model to explore the behaviour of simulated burglars

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Malleson, N., See, L. ORCID: https://orcid.org/0000-0002-2665-7065, Evans, A., & Heppenstall, A.J. (2014). Optimising an agent-based model to explore the behaviour of simulated burglars. In: Theories and Simulations of Complex Social Systems. Eds. Dabbaghian, V. & Mago, V.K., Berlin: Springer. 10.1007/978-3-642-39149-1_12.

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Abstract

Agent-based methods are one approach for modelling complex social systems but one issue with these models is the large number of parameters that require estimation. This chapter examines the effect of using a genetic algorithm (GA) for the parameter estimation of an agent-based model (ABM) of burglary. One of the main issues encountered in the implementation was the computation time required to run the algorithm. Nevertheless a set of preliminary results were obtained, which indicated that visibility is the most important parameter in the decision of whether to burgle a house while accessibility was the least important. Such tools may eventually provide the means to gain a greater understanding of the factors that determine criminological behaviour.

Item Type:	Book Section
Research Programs:	Ecosystems Services and Management (ESM)
Bibliographic Reference:	In: V. Dabbaghian, V.K. Mago (Eds); Theories and Simulations of Complex Social Systems; Springer, Berlin, Heidelberg pp.179-204
Related URLs:	Publisher - http://link.springer.com/book/10.1007%2F978-3-642-39149-1
Depositing User:	IIASA Import
Date Deposited:	15 Jan 2016 08:51
Last Modified:	27 Aug 2021 17:24
URI:	https://pure.iiasa.ac.at/11131

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