TY - JOUR
T1 - Computing the complexity for Schelling segregation models
AU - Gerhold, Stefan
AU - Glebsky, Lev
AU - Schneider, Carsten
AU - Weiss, Howard
AU - Zimmermann, Burkhard
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2008/12
Y1 - 2008/12
N2 - The Schelling segregation models are "agent based" population models, where individual members of the population (agents) interact directly with other agents and move in space and time. In this note we study one-dimensional Schelling population models as finite dynamical systems. We define a natural notion of entropy which measures the complexity of the family of these dynamical systems. The entropy counts the asymptotic growth rate of the number of limit states. We find formulas and deduce precise asymptotics for the number of limit states, which enable us to explicitly compute the entropy.
AB - The Schelling segregation models are "agent based" population models, where individual members of the population (agents) interact directly with other agents and move in space and time. In this note we study one-dimensional Schelling population models as finite dynamical systems. We define a natural notion of entropy which measures the complexity of the family of these dynamical systems. The entropy counts the asymptotic growth rate of the number of limit states. We find formulas and deduce precise asymptotics for the number of limit states, which enable us to explicitly compute the entropy.
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U2 - 10.1016/j.cnsns.2007.04.023
DO - 10.1016/j.cnsns.2007.04.023
M3 - Article
AN - SCOPUS:43049179370
SN - 1007-5704
VL - 13
SP - 2236
EP - 2245
JO - Communications in Nonlinear Science and Numerical Simulation
JF - Communications in Nonlinear Science and Numerical Simulation
IS - 10
ER -