Abstract
In this work, we present a novel evolutionary multiagent-based simulation tool, named as GAPatrol. Such system is devoted to the specification of effective police patrol route strategies for coping with criminal activities happening in a given artificial urban environment, which, in turn, mimics a real demographic region of interest. The approach underlying GAPatrol allows for the automatic uncovering of hotspots and routes of surveillance, which, in real life, are usually discovered by hand with the help of statistical and/or specialized mapping techniques. The qualitative/quantitative results achieved by GAPatrol in two scenarios of study are discussed here, evidencing the potentialities of the novel approach as a promising decision-support tool for police patrolling.
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Reis, D., Melo, A., Coelho, A.L.V., Furtado, V. (2006). GAPatrol: An Evolutionary Multiagent Approach for the Automatic Definition of Hotspots and Patrol Routes. In: Sichman, J.S., Coelho, H., Rezende, S.O. (eds) Advances in Artificial Intelligence - IBERAMIA-SBIA 2006. IBERAMIA SBIA 2006 2006. Lecture Notes in Computer Science(), vol 4140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11874850_16
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DOI: https://doi.org/10.1007/11874850_16
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