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Back to the Future: A Simple Solution to Schelling Segregation

Authors: Sylvain Barde;

Back to the Future: A Simple Solution to Schelling Segregation

Abstract

The maximum entropy methodology is applied to the Schelling model of urban segregation in order to obtain a reliable prediction of the stable configuration of the system without resorting to numerical simulations. We show that this approach also provides an implicit equation describing the distribution of agents over a city which allows for directly assessing the effect of model parameters on the solution. Finally, we discuss the information theoretic motivation for applying this methodology to the Schelling model, and show that it effectively rests on the presence of a potential function, suggesting a broader applicability of the methodology.

Keywords

J15, information theoretic measure, Schelling segregation model, potential function, ddc:330, Information theoretic measure, potential function, Schelling segregation model., C63, D80, Schelling segregation model,Information theoretic measure,potential function,Schelling segregation model., C11, jel: jel:D80, jel: jel:C63, jel: jel:C11, jel: jel:J15

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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