EXTORTION RACKET SYSTEMS AS TARGETS FOR AGENT-BASED SIMULATION MODELS. COMPARING COMPETING SIMULATION MODELS AND EMPRICAL DATA

Abstract

Extortion racketeering is an industry not only practiced by mafia, but also in groups such as hells angels. It occurs in a complex setting of criminals, victims, police and society, and its framework is set up by legal norms as well as informal norms of the actor groups involved. The paper presents two agent-based simulation models which differ with respect to the decision making mode, which is either stochastical with fixed probabilities or deliberative where decisions depend on utility considerations and norms learned during the process. The central research questions of the paper — beside the question how extortion racket system can be appropriately modeled — concern the divergence of the results of the two model versions, the comparison of the input parameter combinations, the motivations of input parameters and the validation of the results by comparing them to available empirical data.