This model explores a social mechanism that links the reversal of the gender gap in education with changing patterns in relative divorce risks in 12 European countries.

This ABM simulates opinions on a topic (originally contested infrastructures) through the interactions between paired agents and based on the sociopsychological assumptions of social judgment theory (SJT; Sherif & Hovland, 1961).

This model is a highly stylized land use model in the Clear Creek Watershed in Eastern Iowa, designed to illustrate the construction of stability landscapes within resilience theory.

A computational model of a classic small group study by Alex Bavelas. This computational model was designed to explore the difficulty in translating a seemingly simple real-world experiment into a computational model.

This agent-based model simulates the diffusion of a social change process stratified by social class in space and time which is solely driven social and spatial variation in communication links.

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

The model explores how two types of information - social (in the form of pheromone trails) and private (in the form of route memories) affect ant colony level foraging in a variable enviroment.

In this Repast model the ‘Consumat’ cognitive framework is applied to an ABM of the Dutch car market. Different policy scenarios can be selected or created to examine their effect on the diffusion of EVs.

The purpose of this model is to enhance a basic ABM through a simple set of rules identified using the activity-driven models in order to produce more realistic patterns of pedestrian movement.

Simulates the construction of scientific journal publications, including authors, references, contents and peer review. Also simulates collective learning on a fitness landscape. Described in: Watts, Christopher & Nigel Gilbert (forthcoming) “Does cumulative advantage affect collective learning in science? An agent-based simulation”, Scientometrics.