The purpose of this model is to investigate the consequences of helminthes in public health policy to eradicate tuberculosis. Helminthes surprise immune system responses and without changes in hygiene

NetLogo implementation of Linear Threshold model of influence propagation.

Due to teacher requests to represent changes in atomic radius, we developed a visualization of the first 36 elements in Netlogo

The Garbage Can Model of Organizational Choice is a fundamental model of organizational decision-making originally proposed by J.D. Cohen, J.G. March and J.P. Olsen in 1972. In the 2000s, G. Fioretti and A. Lomi presented a NetLogo agent-based interpretation of this model. This code is the NetLogo 6.1.1 updated version of the Fioretti-Lomi model.

Positive feedback can lead to “trapping” in local optima. Adding a simple negative feedback effect, based on ant behaviour, prevents this trapping

This model simulates economic and epidemiological interaction between citrus production and the disease Huanglongbing (HLB), which is vectored by the Asian citrus psyllid. The model is used to evaluate area-wide coordinated spraying when free-riding is possible given individuals’ beliefs in other grower participation in area-wide spraying and in the information provided by extension on the threat as HLB spread.

The model attempts to explore the trade-offs between immigration policies and successfully identifying human trafficking victims.

The aim of the model is to define when researcher’s assumptions of dependence or independence of cases in multiple case study research affect the results — hence, the understanding of these cases.

The emergence of cooperation in human societies is often linked to environmental constraints, yet the specific conditions that promote cooperative behavior remain an open question. This study examines how resource unpredictability and spatial dispersion influence the evolution of cooperation using an agent-based model (ABM). Our simulations test the effects of rainfall variability and resource distribution on the survival of cooperative and non-cooperative strategies. The results show that cooperation is most likely to emerge when resources are patchy, widely spaced, and rainfall is unpredictable. In these environments, non-cooperators rapidly deplete local resources and face high mortality when forced to migrate between distant patches. In contrast, cooperators—who store and share resources—can better endure extended droughts and irregular resource availability. While rainfall stochasticity alone does not directly select for cooperation, its interaction with resource patchiness and spatial constraints creates conditions where cooperative strategies provide a survival advantage. These findings offer broader insights into how environmental uncertainty shapes social organization in resource-limited settings. By integrating ecological constraints into computational modeling, this study contributes to a deeper understanding of the conditions that drive cooperation across diverse human and animal systems.

This model simulates the mechanisms of evolution, or how allele frequencies change in a population over time.