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  Subjects -> SOCIOLOGY (Total: 553 journals)
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Journal of Artificial Societies and Social Simulation
Journal Prestige (SJR): 0.565
Citation Impact (citeScore): 2
Number of Followers: 6  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1460-7425
Published by SimSoc Consortium Homepage  [1 journal]
  • An Agent-Based Model to Support Infection Control Strategies at School

    • Authors: paolo.castagno@unito.it (Daniele Baccega; Simone Pernice, Pietro Terna, Paolo Castagno, Giovenale Moirano, Lorenzo Richiardi, Matteo Sereno, Sergio Rabellino, Milena Maria Maule Marco Beccuti
      Abstract: Daniele Baccega, Simone Pernice, Pietro Terna, Paolo Castagno, Giovenale Moirano, Lorenzo Richiardi, Matteo Sereno, Sergio Rabellino, Milena Maria Maule and Marco Beccuti: Many governments enforced physical distancing measures during the COVID-19 pandemic to avoid the collapse of often fragile and overloaded health care systems. Following the physical distancing measures, school closures seemed unavoidable to keep the transmission of the pathogen under control, given the potentially high-risk of these environments. Nevertheless, closing schools was considered an extreme and the last resort of governments, and so various non-pharmaceutical interventions in schools were implemented to reduce the risk of transmission. By means of an agent-based model, we studied the efficacy of active surveillance strategies in the school environment. Simulations settings provided hypothetical although realistic scenarios which allowed us to identify the most suitable control strategy to avoid massive school closures while adapting to contagion dynamics. Reducing risk by means of public policies explored in our study is essential for both health authorities and school administrators.
      PubDate: Fri, 01 Jul 2022 12:59:00 +000
       
  • Structural Effects of Agent Heterogeneity in Agent-Based Models: Lessons
           from the Social Spread of COVID-19

    • Authors: d.cale.reeves@gmail.com (D. Cale Reeves; Nicholas Willems, Vivek Shastry Varun Rai
      Abstract: D. Cale Reeves, Nicholas Willems, Vivek Shastry and Varun Rai: 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.
      PubDate: Fri, 01 Jul 2022 12:58:00 +000
       
  • How Culture Influences the Management of a Pandemic: A Simulation of the
           COVID-19 Crisis

    • Authors: a.ghorbani@tudelft.nl (Kurt Kruelen; Bart de Bruin, Amineh Ghorbani, René Mellema, Christian Kammler, Lois Vanhée, Virginia Dignum Frank Dignum
      Abstract: Kurt Kruelen, Bart de Bruin, Amineh Ghorbani, René Mellema, Christian Kammler, Lois Vanhée, Virginia Dignum and Frank Dignum: Since its first appearance in Wuhan (China), countries have been employing, to varying degrees of success, a series of non-pharmaceutical interventions aimed at limiting the spread of SARS-CoV-2 within their populations. In this article, we build on scientific work that demonstrates that culture is part of the explanation for the observed variability between countries in their ability to effectively control the transmission of SARS-CoV-2. We present a theoretical framework of how culture influences decision-making at the level of the individual. This conceptualization is formalized in an agent-based model that simulates how cultural factors can combine to produce differences across populations in terms of the behavioral responses of individuals to the COVID-19 crisis. We illustrate that, within our simulated environment, the culturally-dependent willingness of people to comply with public health related measures might constitute an important determinant of differences in infection dynamics across populations. Our model generates the highest rates of non-compliance within cultures marked as individualist, progressive and egalitarian. Our model illustrates the potential role of culture as a population-level predictor of infections associated with COVID-19. In doing so, the model, and theoretical framework on which it is based, may inform future studies aimed at incorporating the effect of culture on individual decision-making processes during a pandemic within social simulation models.
      PubDate: Fri, 01 Jul 2022 12:57:00 +000
       
  • Calibrating Agent-Based Models of Innovation Diffusion with Gradients

    • Authors: kotthoff@fortiss.org (Florian Kotthoff; Thomas Hamacher
      Abstract: Florian Kotthoff and Thomas Hamacher: Consumer behavior and the decision to adopt an innovation are governed by various motives, which models find difficult to represent. A promising way to introduce the required complexity into modeling approaches is to simulate all consumers individually within an agent-based model (ABM). However, ABMs are complex and introduce new challenges. Especially the calibration of empirical ABMs was identified as a key difficulty in many works. In this work, a general ABM for simulating the Diffusion of Innovations is described. The ABM is differentiable and can employ gradient-based calibration methods, enabling the simultaneous calibration of large numbers of free parameters in large-scale models. The ABM and calibration method are tested by fitting a simulation with 25 free parameters to the large data set of privately owned photovoltaic systems in Germany, where the model achieves a coefficient of determination of R2 ≃ 0.7.
      PubDate: Fri, 01 Jul 2022 12:56:00 +000
       
  • Integrating Equity Considerations into Agent-Based Modeling: A Conceptual
           Framework and Practical Guidance

    • Authors: tgw@umich.edu (Tim G Williams; Daniel G Brown, Seth D Guikema, Tom M Logan, Nicholas R Magliocca, Birgit Müller Cara E Steger
      Abstract: Tim G Williams, Daniel G Brown, Seth D Guikema, Tom M Logan, Nicholas R Magliocca, Birgit Müller and Cara E Steger: Advancing equity is a complex challenge for society, science, and policy. Agent-based models are increasingly used as scientific tools to advance understanding of systems, inform decision-making, and share knowledge. Yet, equity has not received due attention within the agent-based modeling (ABM) literature. In this paper, we develop a conceptual framework and provide guidance for integrating equity considerations into ABM research and modeling practice. The framework conceptualizes ABM as interfacing with equity outcomes at two levels (the science-society interface and within the model itself) and the modeler as a filter and lens that projects knowledge between the target system and the model. Within the framework, we outline three complementary, equity-advancing action pathways: (1) engage stakeholders, (2) acknowledge positionality and bias, and (3) assess equity with agent-based models. For Pathway 1, we summarize existing guidance within the participatory modeling literature. For Pathway 2, we introduce the positionality and bias document as a tool to promote modeler and stakeholder reflexivity throughout the modeling process. For Pathway 3, we synthesize a typology of approaches for modeling equity and offer a set of preliminary suggestions for best practice. By engaging with these action pathways, modelers both reduce the risks of inadvertently perpetuating inequity and harness the opportunities for ABM to play a larger role in creating a more equitable future.
      PubDate: Fri, 01 Jul 2022 12:55:00 +000
       
  • Egalitarian Sharing Explains Food Distributions in a Small-Scale Society

    • Authors: mppinheiro@gmail.com (Marcos Pinheiro
      Abstract: Marcos Pinheiro: Among social anthropologists, there is virtual consensus that the food-sharing practices of small-scale non-agricultural groups cannot be understood in isolation from the broader repertoire of leveling strategies that prevent would-be dominants from exercising power and influence over likely subordinates. In spite of that widespread view, quantitatively rigorous empirical studies of food sharing and cooperation in small-scale human groups have typically ignored the internal connection between leveling of income and political power, drawing inspiration instead from evolutionary models that are neutral about social role asymmetries. In this paper, I introduce a spatially explicit agent-based model of hunter-gatherer food sharing in which individuals are driven by the goal of maximizing their own income while minimizing income asymmetries among others. Model simulation results show that seven basic patterns of inter-household food transfers described in detail for the Hadza hunters of Tanzania can be simultaneously reproduced with striking accuracy under the assumption that agents selectively support and carry on sharing interactions in ways that maximize their income leveling potential.
      PubDate: Fri, 01 Jul 2022 12:54:00 +000
       
 
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