IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v194y2025ics0960077925001663.html
   My bibliography  Save this article

Complete aging in the noisy voter model enhances consensus formation

Author

Listed:
  • Llabrés, Jaume
  • Oliver-Bonafoux, Sara
  • Anteneodo, Celia
  • Toral, Raúl

Abstract

We investigate the effects of aging in the noisy voter model considering that the probability to change states decays algebraically with age τ, defined as the time elapsed since adopting the current state. We study the complete aging scenario, which incorporates aging to both mechanisms of interaction, herding and idiosyncratic behavior, and compare it with the partial aging case, where aging affects only the herding mechanism. Analytical mean-field equations are derived, finding excellent agreement with agent-based simulations on a complete graph. We observe that complete aging enhances consensus formation, shifting the critical point to higher values compared to the partial aging case. However, when the aging probability decays asymptotically to zero for large τ, a steady state is not always attained for complete aging.

Suggested Citation

  • Llabrés, Jaume & Oliver-Bonafoux, Sara & Anteneodo, Celia & Toral, Raúl, 2025. "Complete aging in the noisy voter model enhances consensus formation," Chaos, Solitons & Fractals, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:chsofr:v:194:y:2025:i:c:s0960077925001663
    DOI: 10.1016/j.chaos.2025.116153
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077925001663
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2025.116153?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2016. "The noisy voter model on complex networks," Papers 1602.06935, arXiv.org, revised Apr 2016.
    2. Peralta, Antonio F. & Khalil, Nagi & Toral, Raúl, 2020. "Ordering dynamics in the voter model with aging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 552(C).
    3. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(1), pages 137-156.
    4. repec:plo:pone00:0209620 is not listed on IDEAS
    5. Granovsky, Boris L. & Madras, Neal, 1995. "The noisy voter model," Stochastic Processes and their Applications, Elsevier, vol. 55(1), pages 23-43, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peralta, Antonio F. & Khalil, Nagi & Toral, Raúl, 2020. "Ordering dynamics in the voter model with aging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 552(C).
    2. Khalil, Nagi & Toral, Raúl, 2019. "The noisy voter model under the influence of contrarians," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 81-92.
    3. Kononovicius, Aleksejus & Astrauskas, Rokas & Radavičius, Marijus & Ivanauskas, Feliksas, 2024. "Delayed interactions in the noisy voter model through the periodic polling mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 652(C).
    4. Aguilar-Janita, Miguel & Blanco-Alonso, Andres & Khalil, Nagi, 2024. "Polarization-induced stress in the noisy voter model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 647(C).
    5. Khalil, Nagi, 2021. "Approach to consensus in models of continuous-opinion dynamics: A study inspired by the physics of granular gases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    6. Eminente, Clara & Artime, Oriol & De Domenico, Manlio, 2022. "Interplay between exogenous triggers and endogenous behavioral changes in contagion processes on social networks," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    7. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2016. "The noisy voter model on complex networks," Papers 1602.06935, arXiv.org, revised Apr 2016.
    8. repec:plo:pone00:0209620 is not listed on IDEAS
    9. Lee, Woosub & Yang, Seong-Gyu & Kim, Beom Jun, 2022. "The effect of media on opinion formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    10. Rytis Kazakevicius & Aleksejus Kononovicius & Bronislovas Kaulakys & Vygintas Gontis, 2021. "Understanding the nature of the long-range memory phenomenon in socioeconomic systems," Papers 2108.02506, arXiv.org, revised Aug 2021.
    11. Moran, José & Fosset, Antoine & Kirman, Alan & Benzaquen, Michael, 2021. "From ants to fishing vessels: a simple model for herding and exploitation of finite resources," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    12. Westerhoff, Frank H. & Dieci, Roberto, 2006. "The effectiveness of Keynes-Tobin transaction taxes when heterogeneous agents can trade in different markets: A behavioral finance approach," Journal of Economic Dynamics and Control, Elsevier, vol. 30(2), pages 293-322, February.
    13. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    14. Frank Westerhoff & Martin Hohnisch, 2010. "Consumer sentiment and countercyclical fiscal policies," International Review of Applied Economics, Taylor & Francis Journals, vol. 24(5), pages 609-618.
    15. Simone Landini & Mauro Gallegati, 2014. "Heterogeneity, interaction and emergence: effects of composition," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(3/4), pages 339-361.
    16. Youwei Li & Xue-Zhong He, 2005. "Long Memory, Heterogeneity, and Trend Chasing," Computing in Economics and Finance 2005 113, Society for Computational Economics.
    17. Reitz, Stefan, 2006. "On the predictive content of technical analysis," The North American Journal of Economics and Finance, Elsevier, vol. 17(2), pages 121-137, August.
    18. Klein, A. & Urbig, D. & Kirn, S., 2008. "Who Drives the Market? Estimating a Heterogeneous Agent-based Financial Market Model Using a Neural Network Approach," MPRA Paper 14433, University Library of Munich, Germany.
    19. Christian Cordes & Stephan Müller & Georg Schwesinger & Sarianna M. Lundan, 2022. "Governance structures, cultural distance, and socialization dynamics: further challenges for the modern corporation," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 371-397, April.
    20. V. Alfi & L. Pietronero & A. Zaccaria, 2008. "Minimal Agent Based Model For The Origin And Self-Organization Of Stylized Facts In Financial Markets," Papers 0807.1888, arXiv.org.
    21. Kudic, Muhamed & Pyka, Andreas & Günther, Jutta, 2012. "Determinants of Evolutionary Change Processes in Innovation Networks – Empirical Evidence from the German Laser Industry," IWH Discussion Papers 7/2012, Halle Institute for Economic Research (IWH).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:194:y:2025:i:c:s0960077925001663. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.