Structural Effects of Agent Heterogeneity in Agent-Based Models: Lessons from the Social Spread of COVID-19

D. Cale Reeves (), Nicholas Willems (), Vivek Shastry () and Varun Rai ()
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Varun Rai: https://lbj.utexas.edu/rai-varun

Journal of Artificial Societies and Social Simulation, 2022, vol. 25, issue 3, 3

Abstract: Modeling human behavior in the context of social systems in which we are embedded realistically requires capturing the underlying heterogeneity in human populations. However, trade-offs associated with different approaches to introducing heterogeneity could either enhance or obfuscate our understanding of outcomes and the processes by which they are generated. Thus, the question arises: how to incorporate heterogeneity when modeling human behavior as part of population-scale phenomena such that greater understanding is obtained? We use an agent-based model to compare techniques of introducing heterogeneity at initialization or generated during the model’s runtime. We show that initializations with unstructured heterogeneity can interfere with a structural understanding of emergent processes, especially when structural heterogeneity might be a key part of driving how behavioral responses dynamically shape emergence in the system. We find that incorporating empirical population heterogeneity – even in a limited sense – can substantially contribute to improved understanding of how the system under study works.

Keywords: Agent-Based Model; Diffusion Model; Empirical Data-Driven Model; Heterogeneous Population; Model Performance; COVID-19 (search for similar items in EconPapers)
Date: 2022-06-30
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Citations: View citations in EconPapers (1)

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