This model is a replication of Torsten Hägerstrand’s 1965 model–one of the earliest known calibrated and validated simulations with implicit “agent based” methodology.

Emulation is one of the simplest and most common mechanisms of social interaction. In this paper we introduce a descriptive computational model that attempts to capture the underlying dynamics of social processes led by emulation.

We built an agent-based model to foster the understanding of homeowners’ insulation activity.

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’.

This models provides the infrastructure to model the activity of making. Individuals use resources they find in their environment plus those they buy, to design, construct and deconstruct items. It represents plans and complex objects explicitly.

The aim of the model is to define when researcher’s assumptions of dependence or independence of cases in multiple case study research affect the results — hence, the understanding of these cases.

The purpose of the OMOLAND-CA is to investigate the adaptive capacity of rural households in the South Omo zone of Ethiopia with respect to variation in climate, socioeconomic factors, and land-use at the local level.

We model the epistemic dynamics preceding political uprising. Before deciding whether to start protests, agents need to estimate the amount of discontent with the regime. This model simulates the dynamics of group knowledge about general discontent.

Simulation-Framework to study the governance of complex, network-like sociotechnical systems by means of ABM. Agents’ behaviour is based on a sociological model of action. A set of basic governance mechanisms helps to conduct first experiments.

The purpose of the Credit and debt market of low-income families model is to help the user examine how the financial market of low-income families works.

The model is calibrated based on real-time data which was collected in a small disadvantaged village in Hungary it contains 159 households’ social network and attributes data.
The simulation models the households’ money liquidity, expenses and revenue structures as well as the formal and informal loan institutions based on their network connections. The model forms an intertwined system integrated in the families’ local socioeconomic context through which families handle financial crises and overcome their livelihood challenges from one month to another.
The simulation-based on the abstract model of low-income families’ financial survival system at the bottom of the pyramid, which was described in following the papers:

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