The Impact of Geometry on Monochrome Regions in the Flip Schelling Process

Thomas Bläsius, T. Friedrich, Martin S. Krejca, Louise Molitor
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引用次数: 1

Abstract

11 Schelling’s classical segregation model gives a coherent explanation for the wide-spread phenomenon 12 of residential segregation. We introduce an agent-based saturated open-city variant, the Flip Schelling 13 Process (FSP), in which agents, placed on a graph, have one out of two types and, based on the 14 predominant type in their neighborhood, decide whether to change their types; similar to a new 15 agent arriving as soon as another agent leaves the vertex. 16 We investigate the probability that an edge { u, v } is monochrome, i.e., that both vertices u and v 17 have the same type in the FSP, and we provide a general framework for analyzing the influence of 18 the underlying graph topology on residential segregation. In particular, for two adjacent vertices, 19 we show that a highly decisive common neighborhood, i.e., a common neighborhood where the 20 absolute value of the difference between the number of vertices with different types is high, supports 21 segregation and, moreover, that large common neighborhoods are more decisive. 22 As an application, we study the expected behavior of the FSP on two common random graph 23 models with and without geometry: (1) For random geometric graphs, we show that the existence of 24 an edge { u, v } makes a highly decisive common neighborhood for u and v more likely. Based on 25 this, we prove the existence of a constant c > 0 such that the expected fraction of monochrome 26 edges after the FSP is at least 1 / 2 + c . (2) For Erdős–Rényi graphs we show that large common 27 neighborhoods are unlikely and that the expected fraction of monochrome edges after the FSP is 28 at most 1 / 2 + o (1). Our results indicate that the cluster structure of the underlying graph has a 29 significant impact on the obtained segregation
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翻转谢林过程中几何形状对单色区域的影响
谢林的经典隔离模型对普遍存在的居住隔离现象给出了连贯的解释。我们引入了一种基于智能体的饱和开放城市变体,即Flip Schelling 13过程(FSP),在该过程中,智能体被放置在一个图上,具有两种类型中的一种,并根据其附近的14种主要类型来决定是否改变其类型;类似于一个新的agent在另一个agent离开顶点时到达。16我们研究了边{u, v}是单色的概率,即两个顶点u和v 17在FSP中具有相同的类型,并且我们提供了一个用于分析底层图拓扑对居住隔离的影响的一般框架。特别是,对于两个相邻的顶点,我们证明了一个高度决定性的共同邻域,即不同类型顶点数量之差的绝对值很高的共同邻域,支持21隔离,而且,大的共同邻域更具决定性。作为一个应用,我们研究了两种常见的随机图23模型上的FSP的期望行为:(1)对于随机几何图,我们证明了边{u, v}的存在使得u和v更有可能具有高度决定性的共同邻域。在此基础上,我们证明了一个常数c > 0的存在性,使得经过FSP后的单色26边的期望分数至少为1 / 2 + c。(2)对于Erdős-Rényi图,我们发现不可能有大的共同邻域,并且FSP后单色边的期望分数最多为1 / 2 + 0(1)。我们的结果表明底层图的聚类结构对获得的隔离有29显著影响
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