Agent-Based Modelling for Criminological Theory Testing and Development addresses the question whether and how we can use simulation methods in order to test criminological theories, and if they fail to be corroborated, how we can use simulation to mend and further develop theories.

It is by no means immediately obvious how results being observed in an artificial environment have any relevance for what is going on in the real world. By using the concept of a "stylized fact," the contributors bridge the gap between artificial and real world. With backgrounds in criminology or artificial intelligence (AI), these contributors present agent-based model studies that test aspects of various theories, including crime pattern theory, guardianship in action theory, near repeat theory, routine activity theory, and general deterrence theory. All six simulation models presented have been specially developed for the book. Contributors have specified the theory, identified stylized facts, developed an agent-based simulation model, let it run, and interpreted whether the chosen stylized fact is occurring in their model, and what we should conclude from congruence or incongruence between simulation and expectations based on the theory under scrutiny. The final chapter discusses what can be learnt from these six enterprises.

The book will be of great interest to scholars of criminology (in particular computational criminologists and theoretical criminologists) and AI (with an emphasis on AI for generative social processes), and more widely researchers in social science in general. It will also be valuable for master''s courses in quantitative criminology.

Agent-Based Modelling for Criminological Theory Testing and Development addresses the question whether and how we can use simulation methods in order to test criminological theories, and if they fail to be corroborated, how we can use simulation to mend and further develop theories.

It is by no means immediately obvious how results being observed in an artificial environment have any relevance for what is going on in the real world. By using the concept of a "stylized fact," the contributors bridge the gap between artificial and real world. With backgrounds in criminology or artificial intelligence (AI), these contributors present agent-based model studies that test aspects of various theories, including crime pattern theory, guardianship in action theory, near repeat theory, routine activity theory, and general deterrence theory. All six simulation models presented have been specially developed for the book. Contributors have specified the theory, identified stylized facts, developed an agent-based simulation model, let it run, and interpreted whether the chosen stylized fact is occurring in their model, and what we should conclude from congruence or incongruence between simulation and expectations based on the theory under scrutiny. The final chapter discusses what can be learnt from these six enterprises.

The book will be of great interest to scholars of criminology (in particular computational criminologists and theoretical criminologists) and AI (with an emphasis on AI for generative social processes), and more widely researchers in social science in general. It will also be valuable for master''s courses in quantitative criminology.