Agent-based modelling as a research tool for criminological research

Abstract

Computational modelling techniques, originating from fields like Computer Science and Artificial Intelligence, may be beneficial for criminological research. Because of their formal nature, computational models can be processed by machines that operate on them, for example for the purpose of simulation. As a consequence, these techniques may help gain insights that lacked based of purely informal theories. A well-known example of such a technique, which has become widely applied within criminology, is called agent-based modelling. Agent-based modelling (ABM) is a computational method that enables a researcher to create, analyse and experiment with models composed of agents, i.e., autonomous pieces of software that interact within a computational environment (Gilbert, 2008). In the current article this technique will be explored in depth. First, I will give a description of the technique and present the architecture of an ABM. Subsequently, I will apply the technique to a simple toy example in the context of a simulation model of the bystander effect, to demonstrate the possibilities of the approach. I will discuss some pros and cons of the approach and present related work to help appreciate the benefits of applying ABM to different criminological research questions. Hopefully, this will provide readers with the necessary knowledge to consider the use of ABM in their own research.

Deter and protect: crime modeling with multi-agent learning

“…Given any successful or failed crime attempts, offender agents update their motivation to commit crime following Eq. (11). After crime events have been computed, each location then updates the beliefs for each agent type using Eqs.…”

“…The ability to model autonomous agents in an environment and then observe the emergent macro level behavior of the system is a natural fit to the interest in the displacement problem. The use of ABM as an acceptable approach to study criminological systems has been reviewed by Birks et al [9], Groff et al [10] and Gerritsen [11]. The originality in using belief learning for agent logic is that the agents learn by observing opposing agents' actions without regard for the payoffs that drove the other agents' choices.…”

How Volunteering Affects the Offender’s Behavior

“…Considering these uses Agent based Modeling is an accommodating tool to study the surfacing of customs and norms in a society [3]. Agent based Modeling has been implemented in social settings to examine the various perspectives affecting the crimes [4].…”

“…The criminologists have examined a variety of aggressive crimes like street robberies [10] [11], civil violence [12] [13]and gang rivalries [14]with the help of Agent based Modeling. Similarly, various research studies have also been performed on the reaction of society to a criminal activity, which keep up a correspondence to the spreading of norms in society [4]. The bystanders" effect [4], which abstain a person from volunteering against a criminal act which he observes, is another example of such situations.…”

“…Similarly, various research studies have also been performed on the reaction of society to a criminal activity, which keep up a correspondence to the spreading of norms in society [4]. The bystanders" effect [4], which abstain a person from volunteering against a criminal act which he observes, is another example of such situations. Some possible reasons for such a behavior diffusion of responsibility, social influence, and audience inhibition are illustrated in [4] with reference of [15].…”