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For each neighborhood j, log wj is the amount of information needed to describe its statistical pattern of income, given that we start by knowing the aggregate income distribution across the city.
Luis M. A. Bettencourt • Introduction to Urban Science: Evidence and Theory of Cities as Complex Systems
will be more intricate, comprehensive, diversified and larger than today’s
Luis M. A. Bettencourt • Introduction to Urban Science: Evidence and Theory of Cities as Complex Systems
generally very robust to the loss of nodes.
Luis M. A. Bettencourt • Introduction to Urban Science: Evidence and Theory of Cities as Complex Systems
model assumptions based on the properties of
Luis M. A. Bettencourt • Introduction to Urban Science: Evidence and Theory of Cities as Complex Systems
Considering the problem of balancing costs and incomes as the primary objective also brings us closer to the experience of single agents (individuals, households, firms, governments).
Luis M. A. Bettencourt • Introduction to Urban Science: Evidence and Theory of Cities as Complex Systems
is this freedom to create new functions, to organize them in networks, and to allocate different amounts of effort across an urban system that will lead to economic growth and the typically exponential growth of incomes in time.
Luis M. A. Bettencourt • Introduction to Urban Science: Evidence and Theory of Cities as Complex Systems
not fall victim to extreme positions of either overgeneralization or sterile particularism.