This agent-based model simulates the lifecycle, movement, and satisfaction of teachers within an urban educational system composed of multiple universities and schools. Each teacher agent transitions through several possible roles: newcomer, university student, unemployed graduate, and employed teacher. Teachers’ pathways are shaped by spatial configuration, institutional capacities, individual characteristics, and dynamic interactions with schools and universities. Universities are assigned spatial locations with a controllable level of centralization and are characterized by academic ratings, capacity, and alumni records. Schools are distributed throughout the city, each with a limited number of vacancies, hiring requirements, and offered salaries. Teachers apply to universities based on the alignment of their personal academic profiles with institutional ratings, pursue studies, and upon graduation become candidates for employment at schools.
The employment process is driven by a decentralized matching of teacher expectations and school offers, taking into account factors such as salary, proximity, and peer similarity. Teachers’ satisfaction evolves over time, reflecting both institutional characteristics and the composition of their colleagues; low satisfaction may prompt teachers to transfer between schools within their mobility radius. Mortality and teacher attrition further shape workforce dynamics, leading to continuous recruitment of newcomers to maintain a stable population. The model tracks university reputation through the academic performance and number of alumni, and visualizes key metrics including teacher status distribution, school staffing, university alumni counts, and overall satisfaction. This structure enables the exploration of policy interventions, hiring and training strategies, and the impact of spatial and institutional design on the allocation, retention, and happiness of urban educational staff.

This is a modified version (Netlogo 4.0.3) of the model in support of Erik Johnstons dissertation, programmed in Netlogo 3.1.4 (May 15th, 2007).

This is a modification of Metaphoria 2019 so that the eternal population is subjected to all the evolutionary forces as the mortal population.

Model that illustrates the use of the GAMA advanced driving skill through a case study concerning the evacuation of the city of Rouen (France).

INOvCWD is a spatially-explicit, agent-based model designed to simulate the spread of chronic wasting disease (CWD) in Indiana’s white-tailed deer populations.

An agent-based model of the Free/Libre Open Source Software (FLOSS) development process designed around agents selecting FLOSS projects to contribute to and/or download.

We provide a full description of the model following the ODD protocol (Grimm et al. 2010) in the attached document. The model is developed in NetLogo 5.0 (Wilenski 1999).

We used a computer simulation to measure how well different network structures (fully connected, small world, lattice, and random) find and exploit resource peaks in a variable environment.

Agents can influence each other if they are close enough in knowledge. The probability to convince with good knowledge and number of agents have an impact on the dissemination of knowledge.

The model is a representation of a liberalised electricity market designed as an energy-only market and consists of large scale investors and their power generation assets in the electricity market.