The model employs an agent-based model for exploring the victim-centered approach to identifying human trafficking and the approach’s effectiveness in an abstract representation of migrant flows.

This is an agent-based model of peer review built on the following three entities: papers, scientists and conferences. The model has been implemented on a BDI platform (Jason) that allows to perform both parameter and mechanism exploration.

This model simulates the household participation in large-scale M. micrantha intervention campaigns and the response of M. micrantha to the intervention.

Dynamic bipartite network model of agents and games in which agents can participate in multiple public goods games.

Merger and acquisition (M&A) activity has many strategic and operational objectives. One operational objective is to develop common and efficient information systems that maybe the source of creating

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.

The purpose of this model is to illustrate the use of agent-based computational modelling in the study of the emergence of reputation and status beliefs in a population.

This is a replication model of the matching problem including the mate search problem, which is the generalization of a traditional optimization problem.

The model is a microsimulation, where the agents don’t Interact with each other. It simulates income distribution, unemployment dynamics, education, and Family grant in Brazil, focusing on the impact on social inequality. It tracks the indicators Gini index, Lorenz curve, and Palma ratio. The objective is to explore how these factors influence wealth distribution and social inequality over time.
This work was developed in partnership with the Graduate Program in Computational Modeling, in the Universidade Federal do Rio Grande - FURG, in Brazil.

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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