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Schelling segregation model shows no critical scaling, study finds

By PulseAugur Editorial · [1 sources] ·

This paper investigates the Schelling segregation model, finding no evidence of critical scaling. The research explored various neighborhood definitions and grid sizes, consistently showing that scaling diagnostics fail to indicate a critical transition. The authors attribute this absence of critical phenomena to the lack of long-range correlation in equilibrium and deterministic dynamics at higher neighbor counts, rather than the model's staircase structure. AI

IMPACT This research contributes to the theoretical understanding of agent-based models, which can inform the design and analysis of AI systems that involve emergent behavior and social dynamics.

RANK_REASON Academic paper detailing a theoretical finding in a simulation model. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Schelling segregation model shows no critical scaling, study finds

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Academic paper detailing a theoretical finding in a simulation model. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Sam Rifaki ·

    Absence of critical scaling in the Schelling segregation model

    We find no evidence of critical scaling in the Schelling segregation model, in either the Moore neighborhood or its dense-spectrum extension to Chebyshev radii up to $r_0 = 6$ ($k = 168$ neighbors). On periodic grids up to $L = 320$ with 50 trials per point (> 12,500 runs), every…

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