Industrial clustering patterns are the result of an entrepreneurial process where spinoffs inherit the ideas and attributes of their parent firms. This computational model maps these patterns using abstract methodologies.

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 simulates diffusion curves and it allows to test how social influence, network structure and consumer heterogeneity affect their spreads and their speeds.

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.

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.

The Opportunistic Acquisition Model (OAM) posits that the archaeological lithic raw material frequencies are due to opportunistic encounters with sources while randomly walking in an environment.

The Netlogo model is a conceptualization of the Moria refugee camp, capturing the household demographics of refugees in the camp, a theoretical friendship network based on values, and an abstraction of their daily activities. The model then simulates how Covid-19 could spread through the camp if one refugee is exposed to the virus, utilizing transmission probabilities and the stages of disease progression of Covid-19 from susceptible to exposed to asymptomatic / symptomatic to mild / severe to recovered from literature. The model also incorporates various interventions - PPE, lockdown, isolation of symptomatic refugees - to analyze how they could mitigate the spread of the virus through the camp.

The simulation model SimPLS shows an application of the PLS agent concept, using SEM as empirical basis for the definition of agent architectures. The simulation model implements the PLS path model TAM about the decision of using innovative products.

The code contains four experiments for well-being based IMRL reward features.

The purpose of the model is to collect information on human decision-making in the context of coalition formation games. The model uses a human-in-the-loop approach, and a single human is involved in each trial. All other agents are controlled by the ABMSCORE algorithm (Vernon-Bido and Collins 2020), which is an extension of the algorithm created by Collins and Frydenlund (2018). The glove game, a standard cooperative game, is used as the model scenario.

The intent of the game is to collection information on the human players behavior and how that compares to the computerized agents behavior. The final coalition structure of the game is compared to an ideal output (the core of the games).