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Model-based reasoning approaches can be used to formalize and analyze (informal) theories from the field of criminology, to help gain more insight in criminological phenomena that were not clear based on just the informal theory. The analysis of the displacement of crime is an important research interest in criminological research. In this chapter, an agent-based simulation model of crime displacement is presented, which can be used not only to simulate the spatiotemporal dynamics of crime, but also to analyze and control those dynamics. Methods are used that are aimed at developing intelligent systems that monitor human-related processes and provide appropriate support. More specifically, an explicit domain model of crime displacement has been developed, and model-based reasoning techniques are applied to the domain model, in order to analyze which environmental circumstances result in which crime rates, and to determine which support measures are most appropriate. The model can be used as an analytical tool for researchers and policy makers to perform thought experiments, that is, to shed more light on the process under investigation, and possibly improve existing policies (e. g., for surveillance).

In this chapter we present some of the central philosophical issues emerging from the increasingly expansive and sophisticated roles computational modeling is playing in the natural and social sciences. Many of these issues concern the adequacy of more traditional philosophical descriptions of scientific practice and accounts of justification for handling computational science, particularly the role of theory in the generation and justification of physical models. However, certain novel issues are also becoming increasingly prominent as a result of the spread of computational approaches, such as nontheory-driven simulations , computational methods of inference, and the important, but often ignored, role of cognitive processes in computational model building.