State of the Art in Agent-Based Modeling of Urban Crime: An Overview (original) (raw)

Agent-Based Simulation of Crime

2013 12th Mexican International Conference on Artificial Intelligence, 2013

The effects of crime are diverse and complex, ranging from psychological and physical traumas faced by crime victims, to negative impacts on the economy of a whole nation. In this paper, an agent-based crime simulation framework to analyze crime and its causes is proposed and implemented. The agent-based simulation framework models and simulates both 1) crime events as a consequence of a set of interrelated social and individual-level crime factors, and 2) crime opportunities, i.e., combinations of circumstances that enable a person to commit a crime. The selection of crime factors and design of agent models are supported by, and based on, existing criminological literature. In addition, the simulation results are validated and compared with macrolevel crime patterns reported by various criminological research efforts.

Comparing Crime Prevention Strategies by Agent-Based Simulation

2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2009

Within the field of Criminology, an important challenge is to investigate the spatio-temporal dynamics of crime. Typical questions in this area are how the emergence of criminal hot spots can be predicted and prevented. This paper presents an agentbased simulation approach that is able to address such questions. More specifically, the approach can be used to compare different strategies for guardian movement in terms of their effectiveness. To illustrate the approach, a number of simulation experiments have been performed, and the results are discussed. † In this paper we focus explicitly on crimes that are performed on the street against random passers-by, e.g. pick-pocketing.

Agent-based vs. population-based simulation of displacement of crime: A comparative study

Web Intelligence and Agent Systems: An International Journal, 2011

Central research questions addressed within Criminology are how the geographical displacement of crime can be understood, explained, and predicted. The process of crime displacement is usually explained by referring to the interaction of three types of agents: criminals, passers-by, and guardians. Most existing simulation models of this process take a 'local' perspective, i.e., they are agent-based. However, when the number of agents considered becomes large, more 'global' approaches, such as population-based simulation have computational advantages over agent-based simulation. This article presents both an agent-based and a population-based simulation model of crime displacement, and reports a comparative evaluation of the two models. In addition, an approach is put forward to analyse the behaviour of both models by means of formal techniques. The results suggest that under certain conditions, population-based models approximate agent-based models, at least in the domain under investigation.

Agent-Based versus Population-Based Simulation of Displacement of Crime: A Comparative Study

2010

Central research questions addressed within Criminology are how the geographical displacement of crime can be understood, explained, and predicted. The process of crime displacement is usually explained by referring to the interaction of three types of agents: criminals, passers-by, and guardians. Most existing simulation models of this process take a 'local' perspective, i.e., they are agent-based. However, when the number of agents considered becomes large, more 'global' approaches, such as population-based simulation have computational advantages over agent-based simulation. This article presents both an agent-based and a population-based simulation model of crime displacement, and reports a comparative evaluation of the two models. In addition, an approach is put forward to analyse the behaviour of both models by means of formal techniques. The results suggest that under certain conditions, population-based models approximate agent-based models, at least in the domain under investigation.

An Agent-Based Model for Public Security Strategies by Predicting Crime Patterns

IEEE Access

In recent years, statistical methods have been applied to the study of crime patterns. However, these schemes have several drawbacks that prevent accurate modeling of complex behaviors. Agent-based models (ABM) allow the modeling of human behavior by employing simple rules that consider each agent's neighborhood. In this paper, a new agent-based model is proposed to emulate crime patterns produced by the interaction of different urban actors, such as offenders (criminals), citizens, and defenders (police officers). Using this approach, the simulation results provide escape trajectories and robbery frequencies that can be used to create or improve public security strategies. Although our scheme can be generically applied, we validated the model by considering different scenarios for the case of Guadalajara, Mexico. Experimental results show that the proposed scheme creates realistic offender behaviors that efficiently predict criminal patterns and provides essential data that allow the creation and improvement of public security strategies to reduce the number of crimes. INDEX TERMS Agent-based model (ABM), crime simulations, crime patterns, routine activity, computer simulation.

Analyzing Crime Displacement with a Simulation Approach

Crime tends to cluster in small areas. Police have taken advantage of this by identifying these “hot spots” of crime and concentrating their resources in these locations. This practice has shown evidence in reducing crime in the hotspot area. While it is possible that the benefits of such reduction be diffused to the surrounding areas, one criticism of this practice is that the crime in the hotspot may be displaced to the surrounding areas. A number of empirical studies have investigated the spatial pattern of crime displacement. However, few attempted to uncover the mechanisms that led to the displacement of crime. This paper presents a theory driven approach that applies agent-based modeling to simulate the mechanism of crime and policing. The processes that drive possible displacement of crime are investigated through experiments in a computational laboratory - SPACES. Our results reveal that crime cannot be easily displaced because opportunities for crime are limited in low crime areas and offenders are often attached to the area where they perform their routine activities.

Comparison of Agent-Based and Population-Based Simulations of Displacement of Crime

2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2008

Within Criminology, the process of crime displacement is usually explained by referring to the interaction of three types of agents: criminals, passersby, and guardians. Most existing simulation models of this process are agent-based. However, when the number of agents considered becomes large, population-based simulation has computational advantages over agent-based simulation. This paper presents both an agent-based and a population-based simulation model of crime displacement, and reports a comparative evaluation of the two models. In addition, an approach is put forward to analyse the behaviour of both models by means of formal techniques.

Can Hot Spots Policing Reduce Crime in Urban Areas? An Agent‐Based Simulation*

Criminology, 2017

Over the past two decades, there has been a growing consensus among researchers that hot spots policing is an effective strategy to prevent crime. Although strong evidence exists that hot spots policing will reduce crime at hot spots without immediate spatial displacement, we know little about its possible jurisdictional or large‐area impacts. We cannot isolate such effects in previous experiments because they (appropriately) compare treatment and control hot spots within large urban communities, thus, confounding estimates of area‐wide impacts. An agent‐based model is used to estimate area‐wide impacts of hot spots policing on street robbery. We test two implementations of hot spots policing (representing different levels of resource allocation) in a simulated borough of a city, and we compare them with two control conditions, one model with constant random patrol and another with no police officers. Our models estimate the short‐ and long‐term impacts on large‐area robbery levels ...

Strengthening Theoretical Testing in Criminology Using Agent-based Modeling

The Journal of research in crime and delinquency, 2014

The Journal of Research in Crime and Delinquency (JRCD) has published important contributions to both criminological theory and associated empirical tests. In this article, we consider some of the challenges associated with traditional approaches to social science research, and discuss a complementary approach that is gaining popularity-agent-based computational modeling-that may offer new opportunities to strengthen theories of crime and develop insights into phenomena of interest. Two literature reviews are completed. The aim of the first is to identify those articles published in JRCD that have been the most influential and to classify the theoretical perspectives taken. The second is intended to identify those studies that have used an agent-based model (ABM) to examine criminological theories and to identify which theories have been explored. Ecological theories of crime pattern formation have received the most attention from researchers using ABMs, but many other criminologica...