This Bicycle encounter model builds on the Salzburg Bicycle model (Wallentin & Loidl, 2015). It simulates cyclist flows and encounters, which are locations of potential accidents between cyclists.

This abstract model explores the emergence of altruistic behavior in networked societies. The model allows users to experiment with a number of population-level parameters to better understand what conditions contribute to the emergence of altruism.

This software simulates cars and bicycles as traffic participants while crossing different crossroad designs such as roundabouts, protected crossroads and standard crossroads. It is written in Netlogo 6.2 and aims to identify safety characteristics of these layouts using agent-based modeling. Participants track the line of sight to each other and print them as an output alongside with the adjacent destination, used layout, count of collisions/cars/bicycles and time.

Detailed information can be found within the info tab of the program itself.

NetLogo implementation of Linear Threshold model of influence propagation.

This generic agent-based model allows the user to simulate and explore the influence of servicising policies on the uptake of servicising and on economic, environmental and social effects, notably absolute decoupling.

The Friendship Field model aims at modelling friendship formation based on three factors: Extraversion, Resemblance and Status, where social interaction is motivated by the Social Battery. Social Battery is one’s energy and motivation to engage in social contact. Since social contact is crucial for friendship formation, the model included Social Battery to affect social interactions. To our best knowledge, Social Battery is a yet unintroduced concept in research while it is a dynamic factor influencing the social interaction besides one’s characteristics. Extraverts’ Social Batteries charge while interacting and exhaust while being alone. Introverts’ Social Batteries charge while being alone and exhaust while interacting. The aim of the model is to illustrate the concept of Social Battery. Moreover, the Friendship Field shows patterns regarding Extraversion, Resemblance and Status including the mere-exposure effect and friendship by similarity. For the implementation of Status, Kemper’s status-power theory is used. The concept of Social Battery is also linked to Kemper’s theory on the organism as reference group. By running the model for a year (3 interactions moments per day), the friendship dynamics over time can be studied.

We presented the model at the Social Simulation Conference 2022.

To investigate the potential of using Social Psychology Theory in ABMs of natural resource use and show proof of concept, we present an exemplary agent-based modelling framework that explicitly represents multiple and hierarchical agent self-concepts

This model illustrates actor interaction in the construction sector, according to information gathered in NL. It offers a simple frame to represent diverse interests, interdependencies and effects on the number of built sustainable houses.

MERCURY aims to represent and explore two descriptive models of the functioning of the Roman trade system that aim to explain the observed strong differences in the wideness of distributions of Roman tableware.

A letter sending model with historically informed initial positions to reconstruct communication and archiving processes in the Republic of Letters, the 15th to 17th century form of scholarship.

The model is aimed at historians, willing to formalize historical assumptions about the letter sending process itself and allows in principle to set heterogeneous social roles, e.g. to evaluate the role of gender or social status in the formation of letter exchange networks. The model furthermore includes a pruning process to simulate the loss of letters to critically asses the role of biases e.g. in relation to gender, geographical regions, or power structures, in the creation of empirical letter archives.

Each agent has an initial random topic vector, expressed as a RGB value. The initial positions of the agents are based on a weighted random draw based on data from [2]. In each step, agents generate two neighbourhoods for sending letters and potential targets to move towards. The probability to send letters is a self-reinforcing process. After each sending the internal topic of the receiver is updated as a movement in abstract space by a random amount towards the letters topic.

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