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).

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.

The model includes different formulations how agents make decisions in irrigation games and this is compared with empirical data. The aim is to test different theoretical models, especially explaining effect of communication.

CoDMER v. 2.0 was parameterized with ethnographic data from organizations dealing with prescribed fire and seeding native plants, to advance theory on how collective decisions emerge in ecological restoration.

The Hohokam Trade Networks Model focuses on key features of the Hohokam economy to explore how differences in trade network topologies may show up in the archaeological record. The model is set in the Phoenix Basin of central Arizona, AD 200-1450.

This is a complex “Data Integration Model”, following a “KIDS” rather than a “KISS” methodology - guided by the available evidence. It looks at the complex mix of social processes that may determine why people vote or not.

We provide an agent-based model of collective action, informed by Granovetter (1978) and its replication model by Siegel (2009). We use the model to examine the role of ICTs in collective action under different cultural and political contexts.

This model uses ’satisficing’ as a model for farmers’ decision making to learn about influences of alternative decision-making models on simulation results and to exemplify a way to transform a rather theoretical concept into a feasible decision-making model for agent-based farming models.

This model allows for analyzing the most efficient levers for enhancing the use of recycled construction materials, and the role of empirically based decision parameters.

We present an agent-based model that maps out and simulates the processes by which individuals within ecological restoration organizations communicate and collectively make restoration decisions.