AN AGENT-BASED APPROACH TO MODELING POLICE PATROL STRATEGIES AND THEIR EFFECTS ON CRIME
Alejandro Camacho, Hye Rin Lee, Laura Smith, Carlos Zambrano.
California State University Fullerton, Fullerton, CA.
In many urban communities, crime is an unfortunate reality for its inhabitants. High levels of crime require law enforcement agencies to optimize their resources to address criminal behaviors. The goal of this project is to extend an agent-based model for crime pattern formation to incorporate police. This approach allows us to simulate criminal and police behaviors. Through these simulations, we can provide a means to test hypothetical policing strategies without costly and unethical experiments. The theories we test incorporate realistic patrolling scenarios and the effect it has on both criminal behavior and the total crime in a region. We compare our results with existing agent-based approaches, such as random patrols and hotspot policing. Using more realistic models, we can test theories to help law enforcement mitigate crime.