The model simulates the spread of a virus through a synthetic network with a degree distribution calibrated on close-range contact data. The model is used to study the macroscopic consequences of cross-individual variability in close-range contact frequencies and to assess whether this variability can be exploited for effective intervention targeting high-contact nodes.

In this model, the spread of a virus disease in a network consisting of school pupils, employed, and umemployed people is simulated. The special feature in this model is the distinction between different types of links: family-, friends-, school-, or work-links. In this way, different governmental measures can be implemented in order to decelerate or stop the transmission.

The Sediba socio-ecolgoical rangeland model is an biomass growth model coupled with a social model of pastoralist behaviour in a commmon pool resource setting. The social subsystem is an empircal ABM.

This model simulates how the strategy one manages time affect the well-being that he/she can obtain.

This is the agent-based model of information market evolution. It simulates the influences of the transition from material to electronic carriers of information, which is modelled by the falling price of variable production factor. It demonstrates that due to zero marginal production costs, the competition increases, the market becomes unstable, and experience various phases of evolution leading to market monopolization.

This model describes a mechanism by which software agents can identify norms in an artificial agent society. In particular, this model uses a sequence mining approach to identify norms in an agent soc

This model simulates the interactions and dynamic trust changes between people which results in social group emergence and evolution.

A spatial prisoner’s dilemma model with mobile agents, de-coupled birth-death events, and harsh environments.

We introduce a model of prediction markets that uses opinion dynamics as its underlying mechanism for price formation. We base the opinion dynamics on the Deffuant model of bounded rationality. We have used this model to show that price formation in prediction markets can be robustly explained by opinion dynamics, and that the model can also explain phase transitions depending on just two parameters.

Fertility Tradeoffs is a NetLogo model that illustrates the emergencent tradeoffs between the quality and quantity of offspring. Often, we associate high fitness with maximizing the number of offspring. However, under certain circumstances, it pays instead to optimize the number of offspring, having fewer offspring than is possible. When the number of offspring is reduced, more energy can be invested in each offspring, which can have fitness benefits.