The model explores the emergence of inequality in cognitive and socio-emotional skills at the societal level within and across generations that results from differences in parental investment behavior during childhood and adolescence.

This is a social trust model for investigating the social relationships and social networks in the real world and in social media.

In recent years we have seen multiple incidents with a large number of people injured and killed by one or more armed attackers. Since this type of violence is difficult to predict, detecting threats as early as possible allows to generate early warnings and reduce response time. In this context, any tool to check and compare different action protocols can be a further step in the direction of saving lives. Our proposal combines features from continuous and discrete models to obtain the best of both worlds in order to simulate large and crowded spaces where complex behavior individuals interact. With this proposal we aim to provide a tool for testing different security protocols under several emergency scenarios, where spaces, hazards, and population can be customized. Finally, we use a proof of concept implementation of this model to test specific security protocols under emergency situations for real spaces. Specifically, we test how providing some users of a university college with an app that informs about the type and characteristics of the ongoing hazard, affects in the safety performance.

HOW IT WORKS

This model consists of three agents, and each agent type operates per business theories as below.
a. New technologies(Tech): It evolves per sustaining or disruptive technology trajectory with the constraint of project management triangle (Scope, Time, Quality, and Cost).
b. Entrepreneurs(Entre): It builds up the solution by combining Tech components per its own strategy (Exploration, Exploitation, or Ambidex).
c. Consumer(Consumer): It selects the solution per its own preference due to Diffusion of innovation theory (Innovators, Early Adopters, Early Majority, Late Majority, Laggards)
…

Agent-based version of the simple search and barter economy conceived by Peter Diamond in 1982. The model is also known as Coconut Model.

The Friendship Field model aims at modelling friendship formation based on three factors: Extraversion, Resemblance and Status, where social interaction is motivated by the Social Battery. Social Battery is one’s energy and motivation to engage in social contact. Since social contact is crucial for friendship formation, the model included Social Battery to affect social interactions. To our best knowledge, Social Battery is a yet unintroduced concept in research while it is a dynamic factor influencing the social interaction besides one’s characteristics. Extraverts’ Social Batteries charge while interacting and exhaust while being alone. Introverts’ Social Batteries charge while being alone and exhaust while interacting. The aim of the model is to illustrate the concept of Social Battery. Moreover, the Friendship Field shows patterns regarding Extraversion, Resemblance and Status including the mere-exposure effect and friendship by similarity. For the implementation of Status, Kemper’s status-power theory is used. The concept of Social Battery is also linked to Kemper’s theory on the organism as reference group. By running the model for a year (3 interactions moments per day), the friendship dynamics over time can be studied.

We presented the model at the Social Simulation Conference 2022.

Social distancing is a strategy to mitigate the spread of contagious disease, but it bears negative impacts on people’s social well-being, resulting in non-compliance. This paper uses an integrated behavioral simulation model, called HUMAT, to identify a sweet spot
that balances strictness of and obedience to social distancing rules.

A novel agent-based model was developed that aims to explore social interaction while it is constrained by visitor limitations (due to Dutch COVID measures). Specifically, the model aims to capture the interaction between the need for social contact and the support for the visitors measure. The model was developed using the HUMAT integrated framework, which offered a psychological and sociological foundation for the behavior of the agents.

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.

This is a relatively simple foraging-radius model, as described first by Robert Kelly, that allows one to quantify the effect of increased logistical mobility (as represented by increased effective foraging radius, r_e) on the likelihood that 2 randomly placed central place foragers will encounter one another within 5000 time steps.

This model is intended to study the way information is collectively managed (i.e. shared, collected, processed, and stored) in a system and how it performs during a crisis or disaster. Performance is assessed in terms of the system’s ability to provide the information needed to the actors who need it when they need it. There are two main types of actors in the simulation, namely communities and professional responders. Their ability to exchange information is crucial to improve the system’s performance as each of them has direct access to only part of the information they need.

In a nutshell, the following occurs during a simulation. Due to a disaster, a series of randomly occurring disruptive events takes place. The actors in the simulation need to keep track of such events. Specifically, each event generates information needs for the different actors, which increases the information gaps (i.e. the “piles” of unaddressed information needs). In order to reduce the information gaps, the actors need to “discover” the pieces of information they need. The desired behavior or performance of the system is to keep the information gaps as low as possible, which is to address as many information needs as possible as they occur.