This multi-model (i.e. a model composed of interacting submodels) is a multi-level representation of a collective motion phenomenon. It was designed to study the impact of the mutual influences between individuals and groups in collective motion.

Building upon the distance-based Hotelling’s differentiation idea, we describe the behavioral experience of several prototypes of consumers, who walk a hypothetical cognitive path in an attempt to maximize their satisfaction.

The agent-based model captures the spatio-temporal institutional dynamics of the economy over the years at the level of a Dutch province. After 1945, Noord-Brabant in the Netherlands has been subject to an active program of economic development through the stimulation of pig husbandry. This has had far-reaching effects on its economy, landscape, and environment. The agents are households. The simulation is at institutional level, with typical stakeholder groups, lobbies, and political parties playing a role in determining policies that in turn determine economic, spatial and ecological outcomes. It allows to experiment with alternative scenarios based on two political dimensions: local versus global issues, and economic versus social responsibilitypriorities. The model shows very strong sensitivity to political context. It can serve as a reference model for other cases where “artificial institutional economics” is attempted.

The simulation is a variant of the “ToRealSim OD variants - base v2.7” base model, which is based on the standard DW opinion dynamics model (but with the differences that rather than one agent per tick randomly influencing another, all agents randomly influence one other per tick - this seems to make no difference to the outcomes other than to scale simulation time). Influence can be made one-way by turning off the two-way? switch

Various additional variations and sources of noise are possible to test robustness of outcomes to these (compared to DW model).
In this version agent opinions change following the empirical data collected in some experiments (Takács et al 2016).

Such an algorithm leaves no role for the uncertainties in other OD models. [Indeed the data from (Takács et al 2016) indicates that there can be influence even when opinion differences are large - which violates a core assumption of these]. However to allow better comparison with other such models there is a with-un? switch which allows uncertainties to come into play. If this is on, then influence (according to above algorithm) is only calculated if the opinion difference is less than the uncertainty. If an agent is influenced uncertainties are modified in the same way as standard DW models.

This proof-of-concept model explores the effects of how social and natural factors are incorporated (factor configuration) in environmentally induced migration. It is built in a conceptual environment where five regions are located in a row.

This model computes the guaranteed viability kernel of a model describing the evolution of a population submitted to successive floods.
The population is described by its wealth and its adaptation rate to floods, the control are information campaigns that have a cost but increase the adaptation rate and the expected successive floods belong to given set defined by the maximal high and the minimal time between two floods.

This model analyzes two investors forming their expectations with heterogeneous strategies in order to optimize their portfolios by means of a Sharpe ratio maximization. Traders are distinguished according to their methodology used in forecasting. Two acknowledged algorithms of technical analysis have been implemented to compare portfolios performances and assess profitability of each technique.

The model represents urban commuters’ transport mode choices among cars, public transit, and motorcycles—a mode highly prevalent in developing countries. Using an agent-based modeling approach, it simulates transport dynamics and serves as a testbed for evaluating policies aimed at improving mobility.

The model simulates an ecosystem of human agents who decide, at each time step, which mode of transportation to use for commuting to work. Their decision is based on a combination of personal satisfaction with their most recent journey—evaluated across a vector of individual needs—the information they crowdsource from their social network, and their personal uncertainty regarding trying new transport options.

Agents are assigned demographic attributes such as sex, age, and income level, and are distributed across city neighborhoods according to their socioeconomic status. To represent social influence in decision-making, agents are connected via a scale-free social network topology, where connections are more likely among agents within the same socioeconomic group, reflecting the tendency of individuals to form social ties with similar others.

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A model to show the effects of flood risk on a housing market; the role of flood protection for risk reduction; the working of the existing public-private flood insurance partnership in the UK, and the proposed scheme ‘Flood Re’.

A friendship game is a kind of network game: a game theory model on a network. This is a NetLogo model of an agent-based adaptation of “‘Friendship-based’ Games” by PJ Lamberson. The agents reach an equilibrium that depends on the strategy played and the topology of the network.