This model examines language dynamics within a social network using simulation techniques to represent the interplay of language adoption, social influence, economic incentives, and language policies. The agent-based model (ABM) focuses on interactions between agents endowed with specific linguistic attributes, who engage in communication based on predefined rules. A key feature of our model is the incorporation of network analysis, structuring agent relationships as a dynamic network and leveraging network metrics to capture the evolving inter-agent connections over time. This integrative approach provides nuanced insights into emergent behaviors and system dynamics, offering an analytical framework that extends beyond traditional modeling approaches. By combining agent-based modeling with network analysis, the model sheds light on the underlying mechanisms governing complex language systems and can be effectively paired with sociolinguistic observational data.

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

We used our model to test how different combinations of dominance interactions present in H. saltator could result in linear, despotic, or shared hierarchies.

We provide a theory-grounded, socio-geographic agent-based model to present a possible explanation for human movement in the Adriatic region within the Cetina phenomenon.

Focusing on ideas of social capital theory from Piere Bordieu (1986), we implement agent mobility in an abstract geography based on cultural capital (prestige) and social capital (social position). Agents hold myopic representations of social (Schaff, 2016) and geographical networks and decide in a heuristic way on moving (and where) or staying.

The model is implemented in a fork of the Laboratory for Simulation Development (LSD), appended with GIS capabilities (Pereira et. al. 2020).

It is very difficult to model a sustainable intergenerational biophysical/financial economy. ModEco NLG is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.

A spatio-temporal Agent Based Modeling (ABM) framework is developed to probabilistically predict farmers’ decisions in the context of climate-induced water scarcity under varying utility optimization functions. The proposed framework forecasts farmers’ behavior assuming varying utility functions. The framework allows decision makers to forecast the behavior of farmers through a user-friendly platform with clear output visualization. The functionality of the proposed ABM is illustrated in an agriculturally dominated plain along the Eastern Mediterranean coastline.

Study area GIS data available upon request to [email protected]

This model played a small part in the UK government’s review of the working of local authority implementation of the Domestic Abuse legislation. The model explicitly represents victim-survivor families as they: (a) try to contact the local DA support system, (b) are triaged by the system and (if there is space) allocated to safe temporary accomodation (c) recieve support services from this position and (d) eventually move on to more permenant accomodation. The purpose of the model was to understand some possible ways in which the implementation of DA Duty, might be frustrated in practice, the identification of gaps in the evidence base and to inform the developing Theory of Change. The key measures used for assessing outcomes in the model were the number of families helped and the services that were delivered to them. The exploration was grounded for in two archetypal cases: that of a relatively immature system for the delivery of DA services and a more mature one (based on actual local authority cases, but not based on any single one). See the official report under associated publications for a summary of results.

EffLab was built to support the study of the efficiency of agents in an evolving complex adaptive system. In particular:
- There is a definition of efficiency used in ecology, and an analogous definition widely used in business. In ecological studies it is called EROEI (energy returned on energy invested), or, more briefly, EROI (pronounced E-Roy). In business it is called ROI (dollars returned on dollars invested).
- In addition, there is the more well-known definition of efficiency first described by Sadi Carnot, and widely used by engineers. It is usually represented by the Greek letter ‘h’ (pronounced as ETA). These two measures of efficiency bear a peculiar relationship to each other: EROI = 1 / ( 1 - ETA )

In EffLab, blind seekers wander through a forest looking for energy-rich food. In this multi-generational world, they live and reproduce, or die, depending on whether they can find food more effectively than their contemporaries. Data is collected to measure their efficiency as they evolve more effective search patterns.

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Studies of colonization processes in past human societies often use a standard population model in which population is represented as a single quantity. Real populations in these processes, however, are structured with internal classes or stages, and classes are sometimes created based on social differentiation. In this present work, information about the colonization of old Providence Island was used to create an agent-based model of the colonization process in a heterogeneous environment for a population with social differentiation. Agents were socially divided into two classes and modeled with dissimilar spatial clustering preferences. The model and simulations assessed the importance of gregarious behavior for colonization processes conducted in heterogeneous environments by socially-differentiated populations. Results suggest that in these conditions, the colonization process starts with an agent cluster in the largest and most suitable area. The spatial distribution of agents maintained a tendency toward randomness as simulation time increased, even when gregariousness values increased. The most conspicuous effects in agent clustering were produced by the initial conditions and behavioral adaptations that increased the agent capacity to access more resources and the likelihood of gregariousness. The approach presented here could be used to analyze past human colonization events or support long-term conceptual design of future human colonization processes with small social formations into unfamiliar and uninhabited environments.