A spatial prisoner’s dilemma model with mobile agents, de-coupled birth-death events, and harsh environments.

An agent-based model which explores Creativity and Urban Development

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

This agent-based model, developed for the study “Online Protest and Repression in Authoritarian Settings,” examines how online protest and repression evolve in authoritarian contexts and how these dynamics affect ordinary users’ attitudes and behavior on social media. The model integrates key theoretical and empirical insights into social media use and core political factors that shape digital contention in authoritarian settings. The following questions are addressed: (1) how online protest–repression dynamics unfold across different levels of authoritarianism and varying compositions of committed accounts, and (2) how ordinary users’ internal propensity to protest and their perceived probability of successful repression change during online protest-repression contestation. The model is evaluated against two empirically grounded macro patterns observed in the real world. The first is enduring protest: online protest becomes dominant as vocal protesters grow to outnumber vocal repressors, shrinking the pool of silent users and stabilizing a pro-protest majority. The second is suppressed protest: online dissent is contained as vocal repression and silence expand in response to protest, yielding a sustained majority of repressive and silent accounts. Together, these dynamics demonstrate how dissenting voices are empowered and suppressed online in authoritarian settings.

The model is used to study the conditions under which agents will cooperate in one-shot two-player Prisoner’s Dilemma games if they are able to withdraw from playing the game and can learn to recogniz

This model can be used to explore under which conditions agents behave as observed in field experiments on irrigation games.

InformalCity, a spatially explicit agent-based model, simulates an artificial city and allows for testing configurations of urban upgrading schemes in informal settlements.

A model of attitudinal dynamics based on the cognitive mechanism of emotional coherence. The code is written in Java. For initialization an additional dataset is required.

The aim of our model is to investigate the team dynamics through two types of task allocation strategies, with a focus on the dynamic interplay between individual needs and group performance. To achieve this goal, we have formulated an agent-based model (ABM) to formalize Deci & Ryan’s self-determination theory (SDT) and explore the social dynamics that govern the relationship between individual and group levels of team performance.

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.