From anarchy to monopoly : how competition and protection shaped mafia's behavior

Mafia-like organizations are highly dynamic and organized criminal groups characterized by their extortive activities that impact societies and economies in different modes and magnitudes. This renders the understanding of how these organizations evolved an objective of both scientific and applicationoriented interests. We propose an agent-based simulation model - the Extortion Racket System model - aimed at understanding the factors and processes explaining the successful settlement of the Sicilian Mafia in Southern Italy, and which may more generally account for the transition from an anarchical situation of uncoordinated extortion to a monopolistic social order. Our results show that in situations of anarchy, these organizations do not last long. This indicates that a monopolistic situation shall be preferred over anarchical ones. Competition is a necessary and sufficient condition for the emergence of a monopolistic situation. However, when competition is combined with protection, the resulting monopolistic regime presents features that make it even more preferable and sustainable for the targets

Countering Protection Rackets Using Legal and Social Approaches: An Agent-Based Test

Protection rackets cause economic and social damage across the world. States typically combat protection rackets using legal strategies that target the racketeers with legislation, strong sentencing, and increasing the presence and involvement of police officers. Nongovernmental organizations, conversely, focus on the rest of the population and counter protection rackets using a social approach. These organisations attempt to change the actions and social norms of community members with education, promotional campaigns, and discussions. We use an agent-based model, which draws on established theories of protection rackets and combines features of sociological and economic perspectives to modelling social interactions, to test the effects of legal and social approaches. We find that a legal approach is a necessary component of a policy approach, that social only approaches should not be used because they lead to large increases in violence, and that a combination of the two works best, although even this must be used carefully

Scientific discovery in a model-centric framework: Reproducibility, innovation, and epistemic diversity

Consistent confirmations obtained independently of each other lend credibility to a scientific result. We refer to results satisfying this consistency as reproducible and assume that reproducibility is a desirable property of scientific discovery. Yet seemingly science also progresses despite irreproducible results, indicating that the relationship between reproducibility and other desirable properties of scientific discovery is not well understood. These properties include early discovery of truth, persistence on truth once it is discovered, and time spent on truth in a long-term scientific inquiry. We build a mathematical model of scientific discovery that presents a viable framework to study its desirable properties including reproducibility. In this framework, we assume that scientists adopt a model-centric approach to discover the true model generating data in a stochastic process of scientific discovery. We analyze the properties of this process using Markov chain theory, Monte Carlo methods, and agent-based modeling. We show that the scientific process may not converge to truth even if scientific results are reproducible and that irreproducible results do not necessarily imply untrue results. The proportion of different research strategies represented in the scientific population, scientists' choice of methodology, the complexity of truth, and the strength of signal contribute to this counter-intuitive finding. Important insights include that innovative research speeds up the discovery of scientific truth by facilitating the exploration of model space and epistemic diversity optimizes across desirable properties of scientific discovery.Comment: EDITS: New title, corrected typos and errors, extended model and results descriptio

Countering Protection Rackets Using Legal and Social Approaches: An Agent-Based Test

Protection rackets cause economic and social damage across the world. States typically combat protection rackets using legal strategies that target the racketeers with legislation, strong sentencing, and increasing the presence and involvement of police officers. Nongovernmental organizations, conversely, focus on the rest of the population and counter protection rackets using a social approach. These organisations attempt to change the actions and social norms of community members with education, promotional campaigns, and discussions. We use an agent-based model, which draws on established theories of protection rackets and combines features of sociological and economic perspectives to modelling social interactions, to test the effects of legal and social approaches. We find that a legal approach is a necessary component of a policy approach, that social only approaches should not be used because they lead to large increases in violence, and that a combination of the two works best, although even this must be used carefully

From anarchy to monopoly : how competition and protection shaped mafia's behavior

Mafia-like organizations are highly dynamic and organized criminal groups characterized by their extortive activities that impact societies and economies in different modes and magnitudes. This renders the understanding of how these organizations evolved an objective of both scientific and applicationoriented interests. We propose an agent-based simulation model - the Extortion Racket System model - aimed at understanding the factors and processes explaining the successful settlement of the Sicilian Mafia in Southern Italy, and which may more generally account for the transition from an anarchical situation of uncoordinated extortion to a monopolistic social order. Our results show that in situations of anarchy, these organizations do not last long. This indicates that a monopolistic situation shall be preferred over anarchical ones. Competition is a necessary and sufficient condition for the emergence of a monopolistic situation. However, when competition is combined with protection, the resulting monopolistic regime presents features that make it even more preferable and sustainable for the targets

An Evacuation Route Model for Disaster Affected Areas

Natural disasters such as earthquake severely damage buildings and introduce obstacles to people trying to evacuate an affected area. Detecting and analyzing the severity of damage to an affected area is a challenge. This paper proposes a novel model for classifying damaged buildings and supporting people's evacuation from natural disaster affected areas using satellite images. The model integrates image segmentation and classification with a shortest path algorithm. First, buildings are detected from pre-disaster satellite images using the proposed Segmentation model. Second, post-disaster images are classified based on the severity of the damage using the proposed Classification model. Finally, the shortest and safest evacuation route to a rescue shelter is detected using the Dijkstra's algorithm. Results show that the Route Detection model dynamically adapts to new and updated satellite images. The Segmentation model shows an F1 score 5% better than the Building Footprint Extraction model and the Classification model shows F1 scores 8% and 10% better than the VGG16 and VGG19 respectively. The Evacuation Route model is useful to disaster management teams and trapped people for planning safe evacuation routes out of the affected area