This model is an extended version of the matching problem including the mate search problem, which is the generalization of a traditional optimization problem. The matching problem is extended to a form of asymmetric two-sided matching problem.

This purpose of this model is to understand how the coupled demographic dynamics of herds and households constrain the growth of livestock populations in pastoral systems.

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.

The model simulates interactions in small, task focused groups that might lead to the emergence of status beliefs among group members.

This model makes it possible to explore how network clustering and resistance to changing existing status beliefs might affect the spontaneous emergence and diffusion of such beliefs as described by status construction theory.

This model implements a Spatial Prisoner’s Dilemma with the option to change whether agents interact deterministically or stochastically.

While the world’s total urban population continues to grow, this growth is not equal. Some cities are declining, resulting in urban shrinkage which is now a global phenomenon. Many problems emerge due to urban shrinkage including population loss, economic depression, vacant properties and the contraction of housing markets. To explore this issue, this paper presents an agent-based model stylized on spatially explicit data of Detroit Tri-county area, an area witnessing urban shrinkage. Specifically, the model examines how micro-level housing trades impact urban shrinkage by capturing interactions between sellers and buyers within different sub-housing markets. The stylized model results highlight not only how we can simulate housing transactions but the aggregate market conditions relating to urban shrinkage (i.e., the contraction of housing markets). To this end, the paper demonstrates the potential of simulation to explore urban shrinkage and potentially offers a means to test polices to alleviate this issue.

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).

MHCABM is an agent-based, multi-hazard risk interaction model with an integrated applied dynamic adaptive pathways planning component. It is designed to explore the impacts of climate change adaptation decisions on the form and function of a coastal human-environment system, using as a case study an idealised patch based representation of the Mount North-Omanu area of Tauranga city, New Zealand. The interacting hazards represented are erosion, inundation, groundwater intrusion driven by intermittent heavy rainfall / inundations (storm) impacts, and sea level rise.

A model that representa farmers potential to adopt bio-fuels in Georgia