A computational model for simulating spatial aspects of crime in urban environments

In this paper, we present a novel approach to computational modeling of social systems. By combining the abstract state machine (ASM) formalism with the multi-agent modeling paradigm, we obtain a formal semantic framework for modeling and integration of established theories of crime analysis and prediction. We focus here on spatial and temporal aspects of crime in urban areas. Our work contributes to a new multidisciplinary research effort broadly classified as Computational Criminology.