MHCABM is an agent-based, multi-hazard risk interaction model with an integrated applied dynamic adaptive pathways planning component. It is designed to explore the impacts of climate change adaptation decisions on the form and function of a coastal human-environment system, using as a case study an idealised patch based representation of the Mount North-Omanu area of Tauranga city, New Zealand. The interacting hazards represented are erosion, inundation, groundwater intrusion driven by intermittent heavy rainfall / inundations (storm) impacts, and sea level rise.

Aqua.MORE (Agent-based MOdelling of REsources in Socio-Hydrological Systems) is an agent based modelling (ABM) approach to simulate the resource flow and social interaction in a coupled natural and social system of water supply and demand. The model is able to simulate the two-way feedback as socio-economic agents influence the natural resource flow and the availability of this resource influences the agents in their behaviour.

This is an opinion dynamics model which extends the model found in (Martins 2009). The previous model had an unshared uncertainty assumption in agent-to-agent interaction this model relaxes that assumption. The model only supports a fully connect network where every agent has an equal likelihood of interacting with every other agent at any given time step. The model is highly modular so different social network paradigm can easier be implemented.

A “Ger” is a yurt style house used by pastoralists in Mongolia. This model simulates seasonal movements, fission/fusion dynamics, social interaction between households and how these relate to climate impacts.

This model examines the economic interaction between Gaulish wheat farmers and Etruscan and Greek wine farming in 7th century B.C. France.

This is a simulation model of communication between two groups of managers in the course of project implementation. The “world” of the model is a space of interaction between project participants, each of which belongs either to a group of work performers or to a group of customers. Information about the progress of the project is publicly available and represents the deviation Earned value (EV) from the planned project value (cost baseline).
The key elements of the model are 1) persons belonging to a group of customers or performers, 2) agents that are communication acts. The life cycle of persons is equal to the time of the simulation experiment, the life cycle of the communication act is 3 periods of model time (for the convenience of visualizing behavior during the experiment). The communication act occurs at a specific point in the model space, the coordinates of which are realized as random variables. During the experiment, persons randomly move in the model space. The communication act involves persons belonging to a group of customers and a group of performers, remote from the place of the communication act at a distance not exceeding the value of the communication radius (MaxCommRadius), while at least one representative from each of the groups must participate in the communication act. If none are found, the communication act is not carried out. The number of potential communication acts per unit of model time is a parameter of the model (CommPerTick).

The managerial sense of the feedback is the stimulating effect of the positive value of the accumulated communication complexity (positive background of the project implementation) on the productivity of the performers. Provided there is favorable communication (“trust”, “mutual understanding”) between the customer and the contractor, it is more likely that project operations will be performed with less lag behind the plan or ahead of it.
The behavior of agents in the world of the model (change of coordinates, visualization of agents’ belonging to a specific communicative act at a given time, etc.) is not informative. Content data are obtained in the form of time series of accumulated communicative complexity, the deviation of the earned value from the planned value, average indicators characterizing communication - the total number of communicative acts and the average number of their participants, etc. These data are displayed on graphs during the simulation experiment.
The control elements of the model allow seven independent values to be varied, which, even with a minimum number of varied values (three: minimum, maximum, optimum), gives 3^7 = 2187 different variants of initial conditions. In this case, the statistical processing of the results requires repeated calculation of the model indicators for each grid node. Thus, the set of varied parameters and the range of their variation is determined by the logic of a particular study and represents a significant narrowing of the full set of initial conditions for which the model allows simulation experiments.
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This model simulates different seeding strategies for information diffusion in a social network adjusted to a case study area in rural Zambia. It systematically evaluates different criteria for seed selection (centrality measures and hierarchy), number of seeds, and interaction effects between seed selection criteria and set size.

The objective of building a social simulation in the Populism and Civic Engagement (PaCE) project is to study the phenomenon of populism by mapping individual level political behaviour and explain the influence of agents on, and their interdependence with the respective political parties. Voters, political parties and – to some extent – the media can be viewed as forming a complex adaptive system, in which parties compete for citizens’ votes, voters decide on which party to vote for based on their respective positions with regard to particular issues, and the media may influence the salience of issues in the public debate.

This is the first version of a model exploring voting behaviour in Austria. It focusses on modelling the interaction of voters and parties in a political landscape; the effects of the media are not yet represented. Austria was chosen as a case study because it has an established populist party (the “Freedom Party” FPO), which has even been part of the government over the years.

The purpose of the model is to simulate the cultural hitchhiking hypothesis to explore how neutral cultural traits linked with advantageous traits spread together over time

The model provides instruments for the simulation of interbank network evolution. There are tools for dynamic network analysis, allowing to evaluate graph topological invariants, thermodynamic network features and combinational node-based features.