GAPatrol: An Evolutionary Multiagent Approach for the Automatic Definition of Hotspots and Patrol Routes

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.