Simple Agents, Complex Emergent City: Agent-Based Modeling of Intraurban Migration - Computational Approaches for Urban Environments - page 139

how complexity arises from actions and interactions of simple agents. There is a
fundamental tension between the desire to create realistic models by incorporating
many urban processes and the desire to explain how features of a city emerge from
the simple interactions among entities such as households and properties (Clarke
2004 ; Brown et al. 2008 ). This tension gives rise to the need for simple, empirically
based agent-based models of migration that can complement the host of more
complicated models. Overall, this approach is deliberately straightforward in that
it does not examine the characteristics of movers or the broader organization of
housing—the primary foci of migration research—but instead centers on combining
long-standing geographical findings to provide a straightforward sociospatial con-
ceptualization of the intraurban migration process. Overall, this work complements
existing approaches while breaking new ground in understanding how individual
behavior scales up to the urban region.
This model also gives insight into how complexity emerges from simplicity
by examining how specific housing opportunities and individual housing search
behavior influence the aggregate pattern of intraurban migration. By combining
intervening opportunities theory with behavioral evidence on the spatial character-
istics of intraurban migration in an agent-based model, we can explore the extent
to which real-world migration patterns can result from simple behavioral rules of
household search in the context of housing opportunities. When households live
in an area with fewer housing opportunities, for example, they are less likely to
find a vacant house that meets their needs and thus require more iterations (i.e.,
more time) to accomplish their housing search. Importantly, while there are many
different conceptual frameworks seek to explain migration, and while this diversity
signifies healthy inquiry, it highlights the need for simple models of individual
actions coupled to broader, generalizable (and admittedly simple) models of urban
processes (Batty 2008 , 2012 ). Methodological challenges abound, as evidenced
by both the large array of statistical and simulation approaches used in migration
analysis and the extent to which they are increasingly combined in hybrid models.
Many of these theoretical and methodological issues have at their heart the need
for better data, particularly on specific individuals and households who collectively
drive intraurban migration. Taken together, these challenges indicate a pressing need
for hybrid statistical and simulation models based on data on specific individuals to
develop stronger conceptual frameworks of how individual actions give rise to the
aggregate patterns and processes of intraurban migration.
Overall, while agent-based modeling can help explain complex systems by
integrating many possible interacting components, it is also a valuable way to
explore how straightforward behavioral rules of individuals can lead to processes
and patterns of complexity. By examining, incorporating, and validating spatial
behavioral theories, the modified intervening opportunities model offered here can
serve as a sociospatial foundation for more comprehensive urban models as well
as contribute to ongoing research on developing and validating theories of human
behavior in urbanization.