Agents are linked in a social-network and make decisions on which of 2 types of behavior to adopt. We explore consequences of different information feedback and providing targeted feedback to individuals.

This model expands approaches from social practice theories and is used to investigate the ability of the underlying conceptual model to explain the emergence of social practices, defined as routine behaviour that is similar amoung peers.

This program simulates a group of hunter-gatherer (households) moving randomly over an artificial landscapoe pulated with resources randomly distributed (a Gaussian distribution). To survive, agents hunt and gather using their own labor resources and available technology. When labor and technology is not enough to compensate the resource difficulty of access, they need to cooperate. The purpose of the model is to analyze the consequences of cooperation on cultural diversity: the more the agents cooperate, the more their culture (a 10 componenet vector) is updated to imitate the culture of cooperative agents. The less the agent cooperates, the more different its culture becomes.

We construct an agent-based model to investigate and understand the roles of green attachment, engagement in local ecological investment (i.e., greening), and social feedback.

The model combines the two elements of disorganization and motivation to explore their impact on teams. Effects of disorganization on team task performance (problem solving)

Plastics and the pollution caused by their waste have always been a menace to both nature and humans. With the continual increase in plastic waste, the contamination due to plastic has stretched to the oceans. Many plastics are being drained into the oceans and rose to accumulate in the oceans. These plastics have seemed to form large patches of debris that keep floating in the oceans over the years. Identification of the plastic debris in the ocean is challenging and it is essential to clean plastic debris from the ocean. We propose a simple tool built using the agent-based modeling framework NetLogo. The tool uses ocean currents data and plastic data both being loaded using GIS (Geographic Information System) to simulate and visualize the movement of floatable plastic and debris in the oceans. The tool can be used to identify the plastic debris that has been piled up in the oceans. The tool can also be used as a teaching aid in classrooms to bring awareness about the impact of plastic pollution. This tool could additionally assist people to realize how a small plastic chunk discarded can end up as large debris drifting in the oceans. The same tool might help us narrow down the search area while looking out for missing cargo and wreckage parts of ships or flights. Though the tool does not pinpoint the location, it might help in reducing the search area and might be a rudimentary alternative for more computationally expensive models.

This model represents informal information transmission networks among medieval Genoese investors used to inform each other about cheating merchants they employed as part of long-distance trade operations.

An empirical ABM of smallholder decisions in times of drought stress.

We model the relationship between natural resource user´s individual time preferences and their use of destructive extraction method in the context of small-scale fisheries.

We extend the Flache-Mäs model to incorporate the location and dyadic communication regime of the agents in the opinion formation process. We make spatially proximate agents more likely to interact with each other in a pairwise communication regime.