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From Schelling to Schools: A Comparison of a Model of Residential Segregation with a Model of School Segregation
By: Victor Ionut Stoica, Andreas Flache, Volume 17 (1)
Abstract: We address theoretically whether and under what conditions Schelling’s celebrated result of ‘self-organized’ unintended residential segregation may also apply to school segregation. We propose here a computational model of school segregation that is aligned with a corresponding Schelling-type model of residential segregation. To adapt the model for application to school segregation, we move beyond previous work by combining two preference arguments in modeling parents’ school choice, preferences for the ethnic composition of a school and preferences for minimizing the travelling distan ...

Combining Segregation and Integration: Schelling Model Dynamics for Heterogeneous Population
By: Erez Hatna, Itzhak Benenson, Volume 18 (4)
Abstract: The Schelling model is a simple agent-based model that demonstrates how individuals’ relocation decisions can generate residential segregation in cities. Agents belong to one of two groups and occupy cells of rectangular space. Agents react to the fraction of agents of their own group within the neighborhood around their cell. Agents stay put when this fraction is above a given tolerance threshold but seek a new location if the fraction is below the threshold. The model is well-known for its tipping point behavior: an initially random (integrated) pattern remains integrated when the toleranc ...

Augmenting Bottom-up Metamodels with Predicates
By: Ross Gore, Saikou Diallo, Christopher Lynch, Jose Padilla, Volume 20 (1)
Abstract: Metamodeling refers to modeling a model. There are two metamodeling approaches for ABMs: (1) top-down and (2) bottom-up. The top down approach enables users to decompose high-level mental models into behaviors and interactions of agents. In contrast, the bottom-up approach constructs a relatively small, simple model that approximates the structure and outcomes of a dataset gathered from the runs of an ABM. The bottom-up metamodel makes behavior of the ABM comprehensible and exploratory analyses feasible. For most users the construction of a bottom-up metamodel entails: (1) creating an experime ...

Space Matters: Extending Sensitivity Analysis to Initial Spatial Conditions in Geosimulation Models
By: Juste Raimbault, Clémentine Cottineau, Marion Le Texier, Florent Le Nechet, Romain Reuillon, Volume 22 (4)
Abstract: Although simulation models of socio-spatial systems in general and agent-based models in particular represent a fantastic opportunity to explore socio-spatial behaviours and to test a variety of scenarios for public policy, the validity of generative models is uncertain unless their results are proven robust and representative of 'real-world' conditions. Sensitivity analysis usually includes the analysis of the effect of stochasticity on the variability of results, as well as the effects of small parameter changes. However, initial spatial conditions are usually not modified systematically in ...