This theoretical model includes forested polygons and three types of agents: forest landowners, foresters, and peer leaders. Agent rules and characteristics were parameterized from existing literature and an empirical survey of forest landowners.

Three policy scenarios for urban expansion under the influences of the behaviours and decision modes of four agents and their interactions have been applied to predict the future development patterns of the Guangzhou metropolitan region.

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

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.

SONG is a simulator designed for simulating the process of transportation network growth.

The simulation model conducts fine-grained population projection by specifying life course dynamics of individuals and couples by means of traditional demographic microsimulation and by using agent-based modeling for mate matching.

We demonstrate how Repast Simphony statecharts can efficiently encapsulate the deep classification hierarchy of the U.S. Air Force for manpower life cycle costing.

This is the R code of the mathematical model that includes the decision making formulations for artificial agents. Plus, the code for graphical output is also added to the original code.

The Sediba socio-ecolgoical rangeland model is an biomass growth model coupled with a social model of pastoralist behaviour in a commmon pool resource setting. The social subsystem is an empircal ABM.

The objective of the model is to evaluate the impact of seasonal forecasts on a farmer’s net agricultural income when their crop choices have different and variable costs and returns.