This Python module contain a function that is able to test the ergodicity of a given agent based model. It is sufficient to produce one long time series and many smaller time series. The function uses

This is the same model as used in the article ‘Modelling Society’s Evolutionary Forces’ except the Fertility graph has been corrected. The Fertility graph was not used in the published article.

The purpose of the model is to generate coalition structures of different glove games, using a specially designed algorithm. The coalition structures can be are later analyzed by comparing them to core partitions of the game used. Core partitions are coalition structures where no subset of players has an incentive to form a new coalition.

The algorithm used in this model is an advancement of the algorithm found in Collins & Frydenlund (2018). It was used used to generate the results in Vernon-Bido & Collins (2021).

The model is designed to simulate the behavior and decision-making processes of individuals (agents) in a social network. It aims to represent the changes in individual probability to take any action based on changes in attributes. The action is anything that can be reasonably influenced by the three influencing methods implemented in this model: peer pressure, social media, and state campaigns, and for which the user has a decision-making model. The model is implemented in the multi-agent programmable environment NetLogo 6.3.0.

This model demonstrates the spread of collapse through a network. The model is abstract but has many applications in various fields.

An agent-based model to investigate the history of irrigated agriculture in the Upper Guadiana Basin, Spain, in order to learn about the influence of farmers’ characteristics (inter alia profit orientation, risk aversion, skills, available labour force and farm size) on land-use change and associated groundwater over-use in this region.

The model was built to study the links between consumer credit, wealth distribution and aggregate demand in a complex macroeconomics system.

This paper builds on a basic ABM for a revolution and adds a combination of behaviors to its agents such as military benefits, citizen’s grievances, geographic vision, empathy, personality type and media impact.

The functioning of an hospital ED. The use case concerns an hospital in Italy which is moving in a new building. Simulations interest both new and old department, to investigate changes by exploring KPIs.

We use an agent-based 3D model to reveal the behavioral dynamics of real-world cases. The target of the simulation is the Peshawar massacre. The previous 2-D model has three main problems which can be solved by our 3-D model. Under the key action rules, our model matches the real target case exactly. Based on the optimal solution, we precisely match the results of the real cases, such as the number of deaths and injuries. We also explore the importance of adding height (constructed as a 3D model) to the model.