Schelling and Sakoda prominently proposed computational models suggesting that strong ethnic residential segregation can be the unintended outcome of a self-reinforcing dynamic driven by choices of individuals with rather tolerant ethnic preferences. There are only few attempts to apply this view to school choice, another important arena in which ethnic segregation occurs. In the current paper, we explore with an agent-based theoretical model similar to those proposed for residential segregation, how ethnic tolerance among parents can affect the level of school segregation. More specifically, we ask whether and under which conditions school segregation could be reduced if more parents hold tolerant ethnic preferences. We move beyond earlier models of school segregation in three ways. First, we model individual school choices using a random utility discrete choice approach. Second, we vary the pattern of ethnic segregation in the residential context of school choices systematically, comparing residential maps in which segregation is unrelated to parents’ level of tolerance to residential maps reflecting their ethnic preferences. Third, we introduce heterogeneity in tolerance levels among parents belonging to the same group. Our simulation experiments suggest that ethnic school segregation can be a very robust phenomenon, occurring even when about half of the population prefers mixed to segregated schools. However, we also identify a “sweet spot” in the parameter space in which a larger proportion of tolerant parents makes the biggest difference. This is the case when parents have moderate preferences for nearby schools and there is only little residential segregation. Further experiments are presented that unravel the underlying mechanisms.

The natural selection of foresight, an accuracy at assess the environment, under degrees of environmental heterogeneity. The model is designed to connect local scale mobility, from foraging, with the global scale phenomenon of population dispersal.

Ants in the genus Temnothorax use tandem runs (rather than pheromone trails) to recruit to food sources. This model explores the collective consequences of this linear recruitment (as opposed to highly nonlinear pheromone trails).

An agent model is presented that aims to capture the impact of cheap talk on collective action in a commons dilemma. The commons dilemma is represented as a spatially explicit renewable resource. Agent’s trust in others impacts the speed and harvesting rate, and trust is impacted by observed harvesting behavior and cheap talk. We calibrated the model using experimental data (DeCaro et al. 2021). The best fit to the data consists of a population with a small frequency of altruistic and selfish agents, and mostly conditional cooperative agents sensitive to inequality and cheap talk. This calibrated model provides an empirical test of the behavioral theory of collective action of Elinor Ostrom and Humanistic Rational Choice Theory.

This study presents a System Dynamics (SD) model that explores the “trajectories of homelessness” among youth outside of the formal care system. Unlike traditional approaches that view runaway behavior as a discrete choice, this model reinterprets it as a neurobiological adaptation to chronic resource deprivation and systemic neglect.
​The model incorporates key mechanisms such as ‘Allostatic Load’ accumulation, ‘PFC-Amygdala Switching’, and the ‘Iatrogenic Effects’ of shelter policies. It utilizes Monte Carlo simulations to demonstrate how structural factors create a “probabilistic vulnerability,” trapping youth in cycles of survival crime and isolation regardless of individual resilience.
​The uploaded code includes a Python implementation of the model to ensure reproducibility of the stochastic analysis presented in the paper.

This generic agent-based model allows the user to simulate and explore the influence of servicising policies on the uptake of servicising and on economic, environmental and social effects, notably absolute decoupling.

This model is to match students and schools using real-world student admission mechanisms. The mechanisms in this model are serial dictatorship, deferred acceptance, the Boston mechanism, Chinese Parallel, and the Taipei mechanism.

Like many developing countries, Nigeria is faced with a number of tradeoffs that pit rapid economic development against environmental preservation. Environmentally sustainable, “green” economic development is slower, more costly, and more difficult than unrestricted, unregulated economic growth. The mathematical model that we develop in this code suggests that widespread public awareness of environmental issues is insufficient to prevent the tendency towards sacrificing the environment for the sake of growth. Even if people have an understanding of negative impacts and always choose to act in their own self-interest, they may still act collectively in such a way as to bring down the quality of life for the entire society. We conclude that additional actions must be taken besides raising public awareness of the environmental problem.

The School Enrollment Model is a spatially-explicit computational model that depicts a city, with schools and students located within the space. The model represents the Chilean school system, a market-based educational system, where people are free to choose among public, private voucher, or private fee-paying schools. In the model, students become aware of some schools, apply to schools, switch schools, pass or fail grade levels, and eventually either graduate or dropout. Schools select students, update their tuition, test scores, and other characteristics.

The purpose of the model is to represent the Chilean school system and analyze the different mechanisms that affected the enrollment distribution between public, private voucher, and private fee-paying school sectors during the period 2004-2016.

This agent-based model simulates how new immigrant households choose where to live in Metro Vancouver under the origins diversity scenario. The model begins with 16,000 household agents, reflecting an expected annual population increase of about 42,500 people based on an average household size of 2.56. Each agent is assigned four characteristics: one of ten origin categories, income level (adjusted using NOC data and recent immigrant earnings), likelihood of having children, and preferred mode of commuting. The ten origin groups are drawn from Census patterns, including six subgroups within the broader Asian category (China, India, the Philippines, Iran, South Korea, and Other Asian countries) and two categories for immigrants from the Americas. This refined classification better captures the diversity of newcomers arriving in the region.