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Thomas Schelling’s classic paper is a key reference point for agent-based models of segregation.  It is often taken as providing fundamental insight into the micro-processes that produce the segregated macro-structures that characterize urban settlement patterns.   In this research tradition, however, urban form plays a very limited role, despite the fact that Schelling himself introduced his model by reference to venues (such as churches) and spatial areas (such as neighbourhoods).   Form is generally reduced to an agent’s capacity to ‘see’ nearby grid-cells of the simulation world: an agent’s neighbourhood is its Moore neighbourhood.

In this research, we argue that an analytically meaningful simulation of neighbourhood formation – or more specifically of integration and segregation dynamics – must acknowledge the role of built form. We introduce a model of physical venues into the classic Schelling model in order to reconsider the simulation’s dynamics as influenced by both the spaces where agents live and the spaces of their activities. Venues structure the urban environment because i) they are foci of interaction and ii) their number and physical distribution constrains agents’ behaviour.  Articulating and observing the consequences of some simple rules for the interaction between agents and venues, we are able to generate characteristic combinations of integration and segregation that have distinctive urban features lacking in typical Schelling-type models.  Moreover, whereas in Schelling-inspired formulations, once a pattern of segregation congeals it is nearly impossible to change, we show that under some circumstances shifting the location of venues may break or redefine underlying patterns to some degree.

In a series of four case studies of increasing sophistication, we observe novel combinations of integration and segregation, brought about by the interaction between agents and venues. In our first study (1), we investigate different spatial configurations of venues from simple geometric distributions to a core and periphery model. Findings highlight the more realistic settlement patterns emerging from the interplay of a planned configuration of venues and the self-organizing behaviour of agents. In our second study (2), we consider variations in a venue’s exclusivity – the extent to which venues of a given group are open to admitting members of other groups. We discuss the parameters under which a range of outcomes result, from integration made possible by adjacent and exclusive venues, to ‘co-opting’ that can be caused by highly inclusive venues. In the third study (3), we build on prior experiments in the literature that have examined unequal populations, and demonstrate how majority/minority dynamics are affected by the presence of physical venues. Finally (4), after noting the high stability of segregated outcomes in Schelling-style simulations, we apply our venue model across a range of parameters in order to evaluate conditions under which settled, segregated neighbourhood patterns become disrupted.

In addition to their particular substantive points, a persistent interest of these studies is whether – and under what parameter ranges – access to group-specific venues allows individual agents to be comfortable remaining in a more diverse neighbourhood vs. these same venues becoming attractors that reinforce Schelling dynamics of segregation. In the process of introducing the case studies, we also describe and deploy a series of methodological innovations. For example, we begin each study with a visualization of the variety of simulation outcomes across value ranges of two input parameters (for example “intolerance threshold” vs. “max travel distance”). These representations, which we refer to throughout as parameter spaces of the simulations, organize the discussions of our findings and allow us to emphasize significant steps or thresholds, where small changes in the input parameters yield large changes in the results (Schelling’s classic example of which is the intolerance threshold around 1/3rd). Where necessary, we also introduce specific techniques of visualization and analysis to effectively characterize the movements of agents and the resulting patterns of clustering in relation to the built form of the simulations.

A working draft of the paper is available here.

attachments
Dynamic_Models_of_Urban_Segregation.pdf