This paper develops a spatial agent-based model to examine how fertility regime shifts reshape population concentration and wealth distribution in an abstract urban system. Migration decisions combine population preference, cultural homophily, expected net income, and resource endowment through a standardised softmax utility. The design is deliberately stylised: it is not calibrated to a particular country or city system, but is intended to isolate the feedbacks linking migration, fertility, urban scaling, and accumulated wealth.
The simulations reveal robust directional asymmetry. When fertility shifts from low to high, population concentration responds rapidly; when fertility shifts from high to low, concentration declines only after a detectable delay and may temporarily continue in the previous direction. Wealth adds a second layer of hysteresis: cell total-wealth concentration follows population concentration with delay, cell mean-wealth inequality and system-level wealth indicators are slower still, and phase-space trajectories form loops rather than collapsing onto a single population–wealth curve. Robustness experiments indicate that longer fertility cycles, wider mobility neighbourhoods, and smoother resource landscapes change the magnitude of delay and overshoot, but do not remove the qualitative asymmetry. The paper argues that demographic decline should be understood not as the mirror image of demographic expansion, but as a path-dependent transition mediated by fast migration-income feedbacks and slower fertility, cohort, culture, and wealth mechanisms.

An agent-based model of one colony of the Florida harvester ant, Pogonomyrmex badius, from the day a mated queen lands to the death of the colony. It runs in a web browser and, unchanged, headless in Node for replicate studies.

What the ants do: a claustral queen digs her own shaft and raises the first workers on her reserves; workers dig the nest under local rules, with no ant holding a plan; a one-way, age-based division of labour set by the season of birth, which no shortage reverses; trunk-trail foraging with site fidelity and recruitment; seed storage, opening and germination in the chambers, which is what feeds the larvae; daily weather from the climate normals of the study site, with drought years; nuptial flights after heavy rain; corpse removal; alarm at a disturbance on the foraging ground; and annual nest relocation, in which the store and then the brood are carried along the trail to a new nest the colony digs.

Every value in the model is tagged as measured in this species, borrowed from another ant, or invented, with its source, in a single parameter file. The model is deterministic: one seeded stream per system and a fixed one-minute timestep, so a seed reproduces a run bit for bit in the browser and in Node, which a test pins. A study writes a methods report listing the invented values the results rest on and the acceptance tests the model fails.

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Explores how social networks affect implementation of institutional rules in a common pool resource.

The Mobility Transition Model (MoTMo) is a large scale agent-based model to simulate the private mobility demand in Germany until 2035. Here, we publish a very much reduced version of this model (R-MoTMo) which is designed to demonstrate the basic modelling ideas; the aim is by abstracting from the (empirical, technological, geographical, etc.) details to examine the feed-backs of individual decisions on the socio-technical system.

In the face of the COVID-19 pandemic, public health authorities around the world have experimented, in a short period of time, with various combinations of interventions at different scales. However, as the pandemic continues to progress, there is a growing need for tools and methodologies to quickly analyze the impact of these interventions and answer concrete questions regarding their effectiveness, range and temporality.

COMOKIT, the COVID-19 modeling kit, is such a tool. It is a computer model that allows intervention strategies to be explored in silico before their possible implementation phase. It can take into account important dimensions of policy actions, such as the heterogeneity of individual responses or the spatial aspect of containment strategies.

In COMOKIT, built using the agent-based modeling and simulation platform GAMA, the profiles, activities and interactions of people, person-to-person and environmental transmissions, individual clinical statuses, public health policies and interventions are explicitly represented and they all serve as a basis for describing the dynamics of the epidemic in a detailed and realistic representation of space.

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The Hohokam Trade Networks Model focuses on key features of the Hohokam economy to explore how differences in trade network topologies may show up in the archaeological record. The model is set in the Phoenix Basin of central Arizona, AD 200-1450.

The Price Evolution with Expectations model provides the opportunity to explore the question of non-equilibrium market dynamics, and how and under which conditions an economic system converges to the classically defined economic equilibrium. To accomplish this, we bring together two points of view of the economy; the classical perspective of general equilibrium theory and an evolutionary perspective, in which the current development of the economic system determines the possibilities for further evolution.

The Price Evolution with Expectations model consists of a representative firm producing no profit but producing a single good, which we call sugar, and a representative household which provides labour to the firm and purchases sugar.The model explores the evolutionary dynamics whereby the firm does not initially know the household demand but eventually this demand and thus the correct price for sugar given the household’s optimal labour.

The model can be run in one of two ways; the first does not include money and the second uses money such that the firm and/or the household have an endowment that can be spent or saved. In either case, the household has preferences for leisure and consumption and a demand function relating sugar and price, and the firm has a production function and learns the household demand over a set number of time steps using either an endogenous or exogenous learning algorithm. The resulting equilibria, or fixed points of the system, may or may not match the classical economic equilibrium.

HousingABM_Japan is a NetLogo agent-based model of the residential market of Tokyo’s 23 wards. It evaluates whether a single parameter configuration can jointly reproduce key features of prices, rents, yields, and market turnover across distinct market regimes from 2001 to 2025, with particular attention to demand- and supply-side trend-following during the 2021–2025 price surge.

The model builds on the Bank of England housing-market lineage (Baptista et al. 2016; Carro et al. 2023) and introduces four extensions: (1) dynamic linkages between the sale and rental markets through vacancy, rents, and yields; (2) heterogeneous demand-side trend-following; (3) supply-side trend-following through construction-cost trend anchoring and a momentum-dependent dynamic premium; and (4) housing-equity borrowing that converts unrealized equity into additional borrowing capacity.

Twenty parameters are calibrated using 2001–2015 data and held fixed for post-calibration evaluation over 2016–2020 and 2021–2025, while annual exogenous inputs follow observed historical paths. The model reproduces the shift from moderate price growth to the 2021–2025 surge, as well as rent acceleration, surge-period yield compression, and persistently low market turnover, although it understates the intermediate acceleration of 2016–2020.

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The agent-based model WEEM (Woodlot Establishment and Expansion Model) as described in the journal article, has been designed to make use of household socio-demographics (household status, birth, and death events of households), to better understand the temporal dynamics of woodlot in the buffer zones of Budongo protected forest reserve, Masindi district, Uganda. The results contribute to a mechanistic understanding of what determines the current gap between intention and actual behavior in forest land restoration at farm level.

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)