We demonstrate how Repast Simphony statecharts can efficiently encapsulate the deep classification hierarchy of the U.S. Air Force for manpower life cycle costing.

We present the Integrated Urban Complexity model (IUCm 1.0) that computes “climate-smart urban forms”, which are able to cut emissions related to energy consumption from urban mobility in half. Furthermore, we show the complex features that go beyond the normal debates about urban sprawl vs. compactness. Our results show how to reinforce fractal hierarchies and population density clusters within climate risk constraints to significantly decrease the energy consumption of urban mobility. The new model that we present aims to produce new advice about how cities can combat climate change. From a technical angle, this model is a geographical automaton, conceptually interfacing between cellular automata and spatial explicit optimisation to achieve normative sustainability goals related to low energy. See a complete user guide at https://iucm.readthedocs.io/en/latest/ .

The model explores how two types of information - social (in the form of pheromone trails) and private (in the form of route memories) affect ant colony level foraging in a variable enviroment.

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.

Fertility Tradeoffs is a NetLogo model that illustrates the emergencent tradeoffs between the quality and quantity of offspring. Often, we associate high fitness with maximizing the number of offspring. However, under certain circumstances, it pays instead to optimize the number of offspring, having fewer offspring than is possible. When the number of offspring is reduced, more energy can be invested in each offspring, which can have fitness benefits.

The model is then used for assessing three hypothetical and contrasted infrastructure-oriented adaptation strategies for the winter tourism industry, that have been previously discussed with local stakeholders, as possible alternatives to the “business-as-usual” situation.

The model is suitable to investigate the effects of different characteristics of apprenticeship programmes both in historical and contemporary societies. The model is built considering five societies, using an agent-based simulation model, we identified six main characteristics which impact the success of an apprenticeship programme in a society, which we measured by considering three parameters, namely the number of skilled agents produced by the apprenticeships, programme completion, and the contribution of programmes in the Gross Domestic Income (GDI) of the society. We investigate different definitions for success of an apprenticeship and some hypothetical societies to test some common beliefs about apprenticeships performance. The model also shows the number of unemployed agents given their work-based skills, wages, and the number of small and large companies who participate in training agents. The model enables exploring the impact of parameters, such as initial wages and the number of training years, along with the stated policies on the system.

NetLogo agent-based model to simulate the transmission of COVID-19 in a university dormitory. User can set the number of initial students, buildings, floors, rooms, number of initially infected, and transmission rate. They can also test the effect of masks, sanitizations, elevator allowance, and visits on the effect of the SEIR curve.

NetLogo implementation of Linear Threshold model of influence propagation.

This model uses preference rankings w.r.t. ethnic group compositions (e.g. at companies) and assigns ethnic agents to groups based on their rankings.