Hierarchical problem-solving model
The model simulates a hierarchical problem-solving process in which a manager delegates parts of a problem to specialists, who attempt to solve specific aspects based on their unique skills. The goal is to examine how effectively the hierarchical structure works in solving the problem, the total cost of the process, and the resulting solution quality.

Problem-solving random network model
The model simulates a network of agents (generalists) who collaboratively solve a fixed problem by iterating over it and using their individual skills to reduce the problem’s complexity. The goal is to study the dynamics of the problem-solving process, including agent interactions, work cycles, total cost, and solution quality.

This is a stylized model based on Alonso’s model investigating the relationship between urban sprawl and income segregation.

The model simulates agents in a spatial environment competing for a common resource that grows on patches. The resource is converted to energy, which is needed for performing actions and for surviving.

Resilience of humans in the Upper Paleolithic could provide insights in how to defend against today’s environmental threats. Approximately 13,000 years ago, the Laacher See volcano located in present-day western Germany erupted cataclysmically. Archaeological evidence suggests that this is eruption – potentially against the background of a prolonged cold spell – led to considerable culture change, especially at some distance from the eruption (Riede, 2017). Spatially differentiated and ecologically mediated effects on contemporary social networks as well as social transmission effects mediated by demographic changes in the eruption’s wake have been proposed as factors that together may have led to, in particular, the loss of complex technologies such as the bow-and-arrow (Riede, 2014; Riede, 2009).

This model looks at the impact of the interaction between climate change trajectory and an extreme event, such as the Laacher See eruption, on the generational development of hunter-gatherer bands. Historic data is used to model the distribution and population dynamics of hunter-gatherer bands during these circumstances.

This model is based on the Narragansett Bay, RI recreational fishery. The two types of agents are piscivorous fish and fishers (shore and boat fishers are separate “breeds”). Each time step represents one week. Open season is weeks 1-26, assuming fishing occurs during half the year. At each weekly time step, fish agents grow, reproduce, and die. Fisher agents decide whether or not to fish based on their current satisfaction level, and those that do go fishing attempt to catch a fish. If they are successful, they decide whether to keep or release the fish. In our publication, this model was linked to an Ecopath with Ecosim food web model where the commercial harvest of forage fish affected the biomass of piscivorous fish - which then became the starting number of piscivorous fish for this ABM. The number of fish caught in a season of this ABM was converted to a fishing pressure and input back into the food web model.

Style_Net_01 is a spatial agent-based model designed to serve as a platform for exploring geographic patterns of tool transport and discard among seasonally mobile hunter-gatherer populations. The model has four main levels: artifact, person, group, and system. Persons make, use, and discard artifacts. Persons travel in groups within the geographic space of the model. The movements of groups represent a seasonal pattern of aggregation and dispersal, with all groups coalescing at an aggregation site during one point of the yearly cycle. The scale of group mobility is controlled by a parameter. The creation, use, and discard of artifacts is controlled by several parameters that specify how many tools each person carries in a personal inventory, how many times each tool can be used before it is discarded, and the frequency of tool usage. A lithic source (representing a geographically-specific, recognizable source of stone for tools) can be placed anywhere in the geographic space of the model.

The purpose of the model is to explore how processes associated with compliance across different fishery actors’ social groups interplay with their acceptance of a fishery intervention, herein periodic closures of a small-scale octopus fishery. The model agents, entities and processes are designed based on stylized facts from literature and expert workshops on periodic closures in the Western Indian Ocean region, as well as fieldwork from Zanzibari villages that have implemented periodic octopus closures. The model is designed for scientists and decision-makers that are interested in understanding the complex interplay between fishers from different social groups, herein foot fisher men, foot fisher women and male skin divers or free divers within the periodic closure of an octopus species. Including various actions resulting from the restrictions, that is - opportunities that may be presented from restricting fishing in certain areas and during certain times. We are soon publishing an updated model with individual octopuses and their movement behaviors.

The TechNet_04 is an abstract model that embeds a simple cultural tranmission process in an environment where interaction is structured by spatially-situated networks.

MELBIS-V1 is a spatially explicit agent-based model that allows the geospatial simulation of the decision-making process of newcomers arriving in the bilingual cities and boroughs of the island of Montreal, Quebec in CANADA, and the resulting urban segregation spatial patterns. The model was implemented in NetLogo, using geospatial raster datasets of 120m spatial resolution.

MELBIS-V2 enhances MELBIS-V1 to implement and simulate the decision-making processes of incoming immigrants, and to analyze the resulting spatial patterns of segregation as immigrants arrive and settle in various cities in Canada. The arrival and segregation of immigrants is modeled with MELBIS-V2 and compared for three major Canadian immigration gateways, including the City of Toronto, Metro Vancouver, and the City of Calgary.

This is an interdisciplinary agent-based model with Monte Carlo simulations to assess the relative effects of broadcast and contagion processes in a multiplex social network. This multiplex approach models multiple channels of informal communication - phone, word-of-mouth, and social media - that vary in their attribute values. Each agent is an individual in a threatened community who, once warned, has a probability of warning others in their social network using one of these channels. The probability of an individual warning others is based on their warning source and the time remaining until disaster impact, among other variables. Default parameter values were chosen from empirical studies of disaster warnings along with the spatial aspects of Coos Bay, OR, USA and Seaside, OR, USA communities.