This model represents individuals from two different groups interacting and sharing attitudes toward both groups. Through these interactions, individuals adjust their attitudes, which can lead to different outcomes in opinion dynamics. The model can study both intra-group and inter-group opinion dynamics. Under certain conditions, agents with initially moderate attitudes might enter a negative spiral, leading to increasingly extreme intergroup attitudes. Alternatively, these moderate attitudes can foster consensus between groups, resulting in agreement on intergroup attitudes. This model serves as a tool for exploring opinion polarization, particularly in contexts where attitudes evolve through interaction rather than remaining static.

By adjusting different parameters, one can examine the effects of variations in attitude distributions; group size and relative group size; contributions of xenophobia, opinion distance, and individual attitudes towards the outgroup; as well as ratio between xenophobia and attitudinal bias to the overall intergroup bias.

The model accompanies the paper When contact backfires, and when it does not: A computational model of the opinion dynamics of intergroup attitudes.

This is a Netlogo model which simulates car and bus/tram traffic in Augsburg, specifically between the districts Stadtbergen, Göggingen and the Königsplatz. People either use their cars or public transport to travel to one of their random destinations (Stadtbergen or Göggingen), performing some activity and then returning to their home. Attributes such as travel and waiting time as well as their happiness upon arriving are stored and have an impact on individuals on whether they would consider changing their mode of transport or not.

This ABM aims to introduce a new individual decision-making model, BNE into the ABM of pedestrian evacuation to properly model individual behaviours and motions in emergency situations. Three types of behavioural models has been developed, which are Shortest Route (SR) model, Random Follow (RF) model, and BNE model, to better reproduce evacuation dynamics in a tunnel space. A series of simulation experiments were conducted to evaluate the simulating performance of the proposed ABM.

Viking Sailing is a spatially explicit agent-based simulation for conditional exploration of how rasterized coastlines, wind, and
surface-current conditions interact with simplified ship movement, sailing, rowing, navigation, and land-avoidance rules. The
model compares simulated route trajectories and terminal outcomes for hypothetical Viking-era small-ship voyages. It includes an example dataset representing sea surface winds and currents from June 1000 CE. Additional data can are downloaded from Zenodo: https://zenodo.org/records/23213147.

The core algorithm is an agent-based model, which simulates travel patterns on a network based on microscopic decision-making by each traveler.

An ABM to simulate the spatio-temporal distribution of cyclists across the road network of the city of Salzburg.

This is an adaptation and extension of Robert Axtell’s model (2013) of endogenous firms, in Python 3.4

Swidden Farming is designed to explore the dynamics of agricultural land management strategies.

This BNE-informed ABM ultimately aims to provide a more realistic description of complicated pedestrian behaviours especially in high-density and life-threatening situations. Bayesian Nash Equilibrium (BNE) was adopted to reproduce interactive decision-making process among rational and game-playing agents. The implementations of 3 behavioural models, which are Shortest Route (SR) model, Random Follow (RF) model, and BNE model, make it possible to simulate emergent patterns of pedestrian behaviours (e.g. herding and self-organised queuing behaviours, etc.) in emergency situations.

According to the common features of previous mass trampling accidents, a series of simulation experiments were performed in space with 3 types of barriers, which are Horizontal Corridors, Vertical Corridors, and Random Squares, standing for corridors, bottlenecks and intersections respectively, to investigate emergent behaviours of evacuees in varied constricted spatial environments. The output of this ABM has been available at https://data.mendeley.com/datasets/9v4byyvgxh/1.

A demonstration model showing how modellers can create a multi regional tram network with commuters, destinations and houses. The model offers options to create a random tram network made from modeller input or to load shapefiles for the Greater Manchester Metrolink.

The model uses NetLogo with gis, nw an csv extensions.