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Control of the socio-economic systems using herding interactions

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  • Aleksejus Kononovicius
  • Vygintas Gontis

Abstract

Collective behavior of the complex socio-economic systems is heavily influenced by the herding, group, behavior of individuals. The importance of the herding behavior may enable the control of the collective behavior of the individuals. In this contribution we consider a simple agent-based herding model modified to include agents with controlled state. We show that in certain case even the smallest fixed number of the controlled agents might be enough to control the behavior of a very large system.

Suggested Citation

  • Aleksejus Kononovicius & Vygintas Gontis, 2013. "Control of the socio-economic systems using herding interactions," Papers 1309.6105, arXiv.org, revised Feb 2014.
    • Handle: RePEc:arx:papers:1309.6105
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    References listed on IDEAS

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    1. Robert Axelrod, 1997. "Advancing the Art of Simulation in the Social Sciences," Working Papers 97-05-048, Santa Fe Institute.
    2. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(1), pages 137-156.
    3. Kononovicius, A. & Gontis, V., 2012. "Agent based reasoning for the non-linear stochastic models of long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1309-1314.
    4. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2008. "Time variation of higher moments in a financial market with heterogeneous agents: An analytical approach," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 101-136, January.
    5. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 19-49, August.
    6. Alfarano, Simone & Milakovic, Mishael, 2009. "Network structure and N-dependence in agent-based herding models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 78-92, January.
    7. M. Cristelli & L. Pietronero & A. Zaccaria, 2011. "Critical Overview of Agent-Based Models for Economics," Papers 1101.1847, arXiv.org.
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    Cited by:

    1. Aleksejus Kononovicius & Vygintas Gontis, 2014. "Herding interactions as an opportunity to prevent extreme events in financial markets," Papers 1409.8024, arXiv.org, revised May 2015.
    2. Vygintas Gontis & Aleksejus Kononovicius, 2014. "Consentaneous Agent-Based and Stochastic Model of the Financial Markets," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-12, July.
    3. 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.
    4. Christopher M Wray & Steven R Bishop, 2016. "A Financial Market Model Incorporating Herd Behaviour," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-28, March.

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