We present an Agent-Based Stock Flow Consistent Multi-Country model of a Currency Union to analyze the impact of changes in the fiscal regimes that is permanent changes in the deficit-to-GDP targets that governments commit to comply.

The model that simulates the dynamic creation and maintenance of knowledge-based formations such as communities of scientists, fashion movements, and subcultures. The model’s environment is a spatial one, representing not geographical space, but a “knowledge space” in which each point is a different collection of knowledge elements. Agents moving through this space represent people’s differing and changing knowledge and beliefs. The agents have only very simple behaviors: If they are “lonely,” that is, far from a local concentration of agents, they move toward the crowd; if they are crowded, they move away.

Running the model shows that the initial uniform random distribution of agents separates into “clumps,” in which some agents are central and others are distributed around them. The central agents are crowded, and so move. In doing so, they shift the centroid of the clump slightly and may make other agents either crowded or lonely, and they too will move. Thus, the clump of agents, although remaining together for long durations (as measured in time steps), drifts across the view. Lonely agents move toward the clump, sometimes joining it and sometimes continuing to trail behind it. The clumps never merge.

The model is written in NetLogo (v6). It is used as a demonstration of agent-based modelling in Gilbert, N. (2008) Agent-Based Models (Quantitative Applications in the Social Sciences). Sage Publications, Inc. and described in detail in Gilbert, N. (2007) “A generic model of collectivities,” Cybernetics and Systems. European Meeting on Cybernetic Science and Systems Research, 38(7), pp. 695–706.

The Palaeo-Agulhas Plain formed an important habitat exploited by Pleistocene hunter-gatherer populations during periods of lower sea level. This productive, grassy habitat would have supported numerous large-bodied ungulates accessible to a population of skilled hunters with the right hunting technology. It also provided a potentially rich location for plant food collection, and along its shores a coastline that moved with the rise and fall of sea levels. The rich archaeological and paleontological records of Pleistocene sites along the modern Cape south coast of South Africa, which would have overlooked the Palaeo-Agulhas Plain during Pleistocene times of lower sea level, provides a paleoarchive of this extinct ecosystem. In this paper, we present a first order illustration of the “palaeoscape modeling” approach advocated by Marean et al. (2015). We use a resourcescape model created from modern studies of habitat productivity without the Palaeo-Agulhas Plain. This is equivalent to predominant Holocene conditions. We then run an agent-based model of the human foraging system to investigate several research questions. Our agent-based approach uses the theoretical framework of optimal foraging theory to model human foraging decisions designed to optimize the net caloric gains within a complex landscape of spatially and temporally variable resources. We find that during the high sea-levels of MIS 5e (+5-6 m asl) and the Holocene, the absence of the Plain left a relatively poor food base supporting a much smaller population relying heavily on edible plant resources from the current Cape flora. Despite high species diversity of plants with edible storage organs, and marine invertebrates, encounter rates with highly profitable resources were low. We demonstrate that without the Palaeo-Agulhas Plain, human populations must have been small and low density, and exploited plant, mammal, and marine resources with relatively low caloric returns. The exposure and contraction of the Palaeo-Agulhas Plain was likely the single biggest driver of behavioral change during periods of climate change through the Pleistocene and into the transition to the Holocene.

The Carington model is designed to provide insights into the factors affecting informal health care for older adults. It encompasses older adults, caregivers, and factors affecting informal health care. The Carington model includes no submodels.

The Pampas Model is an Agent-Based Model intended to explore the dynamics of structural and land use changes in agricultural systems of the Argentine Pampas in response to climatic, technological economic, and political drivers.

Patagonia PSMED is an agent-based model designed to study a simple case of Evolution of Ethnic Differentiation. It replicates how can hunter-gatherer societies evolve and built cultural identities as a consequence of the way they interacted.

Non-traditional tools and mediums can provide unique methodological and interpretive opportunities for archaeologists. In this case, the Unreal Engine (UE), which is typically used for games and media, has provided a powerful tool for non-programmers to engage with 3D visualization and programming as never before. UE has a low cost of entry for researchers as it is free to download and has user-friendly “blueprint” tools that are visual and easily extendable. Traditional maritime mobility in the Salish Sea is examined using an agent-based model developed in blueprints. Focusing on the sea canoe travel of the Straits Salish northwestern Washington State and southwest British Columbia. This simulation integrates GIS data to assess travel time between Coast Salish archaeological village locations and archaeologically represented resource gathering areas. Transportation speeds informed by ethnographic data were used to examine travel times for short forays and longer inter-village journeys. The results found that short forays tended to half day to full day trips when accounting for resource gathering activities. Similarly, many locations in the Salish Sea were accessible in long journeys within two to three days, assuming fair travel conditions. While overall transportation costs to reach sites may be low, models such as these highlight the variability in transport risk and cost. The integration of these types of tools, traditionally used for entertainment, can increase the accessibility of modeling approaches to researchers, be expanded to digital storytelling, including aiding in the teaching of traditional ecological knowledge and placenames, and can have wide applications beyond maritime archaeology.

This is v0.01 of a UE5.2.1 agent based model.

A system that receives from an agent-based social simulation the agent’s emotional data, their emotional-related data such as motivations and beliefs, as well as their location, and visualizes of all this information in a two dimensional map of the geographic region the agents inhabit as well as on graphs along the time dimension.

This is an agent-based model of the implementation of the self-enforcing agreement in cooperative teams.

In this agent-based model, agents decide to adopt a new product according to a utility function that depends on two kinds of social influences. First, there is a local influence exerted on an agent by her closest neighbors that have already adopted, and also by herself if she feels the product suits her personal needs. Second, there is a global influence which leads agents to adopt when they become aware of emerging trends happening in the system. For this, we endow agents with a reflexive capacity that allows them to recognize a trend, even if they can not perceive a significant change in their neighborhood.

Results reveal the appearance of slowdown periods along the adoption rate curve, in contrast with the classic stylized bell-shaped behavior. Results also show that network structure plays an important role in the effect of reflexivity: while some structures (e.g., scale-free networks) may amplify it, others (e.g., small-world structure) weaken such an effect.