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Swarm intelligence in humans: A perspective of emergent evolution

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  • Tao, Yong

Abstract

The origin of intelligence has fascinated scientists for a long time. Over the past 100 years, many scholars have observed the connection between entropy and intelligence. In the present study, we investigated a potential origin of the swarm intelligence in humans. The present study shows that a competitive economy consisting of a large number of self-interested agents can be mapped to a Boltzmann-like system, where entropy and energy play roles of swarm intelligence and income, respectively. However, different from the physical entropy in the Boltzmann system, the entropy (or swarm intelligence) in the economic system is a self-referential variable, which may be a key characteristic for distinguishing between biological and physical systems. Furthermore, we employ the household income data from 66 countries and Hong Kong SAR to test the validity of the Boltzmann-like distribution. Remarkably, the empirical data are perfectly consistent with the theoretical results. This finding implies that the competitive behaviors among a colony of self-interested agents will spontaneously prompt the colony to evolve to a state of higher technological level, although each agent has no willingness to evolve.

Suggested Citation

  • Tao, Yong, 2018. "Swarm intelligence in humans: A perspective of emergent evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 436-446.
    • Handle: RePEc:eee:phsmap:v:502:y:2018:i:c:p:436-446
    DOI: 10.1016/j.physa.2018.02.120
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    References listed on IDEAS

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    1. Yong Tao & Xiangjun Wu & Tao Zhou & Weibo Yan & Yanyuxiang Huang & Han Yu & Benedict Mondal & Victor M. Yakovenko, 2019. "Exponential structure of income inequality: evidence from 67 countries," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 345-376, June.
    2. Mas-Colell, Andreu & Whinston, Michael D. & Green, Jerry R., 1995. "Microeconomic Theory," OUP Catalogue, Oxford University Press, number 9780195102680.
    3. Tao, Yong, 2015. "Universal laws of human society’s income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 435(C), pages 89-94.
    4. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    5. Yong Tao, 2015. "Universal Laws of Human Society's Income Distribution," Papers 1506.05418, arXiv.org.
    6. Herbert A. Simon, 1991. "Bounded Rationality and Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 125-134, February.
    7. Yong Tao, 2010. "Competitive market for multiple firms and economic crisis," Papers 1010.1413, arXiv.org.
    8. Victor M. Yakovenko & J. Barkley Rosser, 2009. "Colloquium: Statistical mechanics of money, wealth, and income," Papers 0905.1518, arXiv.org, revised Dec 2009.
    9. Yong Tao, 2016. "Spontaneous economic order," Journal of Evolutionary Economics, Springer, vol. 26(3), pages 467-500, July.
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    Cited by:

    1. Tao, Yong & Lin, Li & Wang, Hanjie & Hou, Chen, 2023. "Superlinear growth and the fossil fuel energy sustainability dilemma: Evidence from six continents," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 39-51.
    2. Karataieva, Tatiana & Koshmanenko, Volodymyr & Krawczyk, Małgorzata J. & Kułakowski, Krzysztof, 2019. "Mean field model of a game for power," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 535-547.
    3. Romain Bocher, 2023. "Causal Entropic Forces, Narratives and Self-organisation of Capital Markets," Journal of Interdisciplinary Economics, , vol. 35(2), pages 172-190, July.
    4. Tao, Yong & Sornette, Didier & Lin, Li, 2021. "Emerging social brain: A collective self-motivated Boltzmann machine," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    5. Tao, Yong, 2020. "Self-referential Boltzmann machine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    6. Maia, Adriano & Matsushita, Raul & Da Silva, Sergio, 2020. "Earnings distributions of scalable vs. non-scalable occupations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    7. Tao, Yong, 2021. "Boltzmann-like income distribution in low and middle income classes: Evidence from the United Kingdom," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    8. Li, Munan & Porter, Alan L. & Suominen, Arho & Burmaoglu, Serhat & Carley, Stephen, 2021. "An exploratory perspective to measure the emergence degree for a specific technology based on the philosophy of swarm intelligence," Technological Forecasting and Social Change, Elsevier, vol. 166(C).

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