IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2404.10554.html
   My bibliography  Save this paper

Quantum Mechanics of Human Perception, Behaviour and Decision-Making: A Do-It-Yourself Model Kit for Modelling Optical Illusions and Opinion Formation in Social Networks

Author

Listed:
  • Ivan S. Maksymov

Abstract

On the surface, behavioural science and physics seem to be two disparate fields of research. However, a closer examination of problems solved by them reveals that they are uniquely related to one another. Exemplified by the theories of quantum mind, cognition and decision-making, this unique relationship serves as the topic of this chapter. Surveying the current academic journal papers and scholarly monographs, we present an alternative vision of the role of quantum mechanics in the modern studies of human perception, behaviour and decision-making. To that end, we mostly aim to answer the 'how' question, deliberately avoiding complex mathematical concepts but developing a technically simple computational code that the readers can modify to design their own quantum-inspired models. We also present several practical examples of the application of the computation code and outline several plausible scenarios, where quantum models based on the proposed do-it-yourself model kit can help understand the differences between the behaviour of individuals and social groups.

Suggested Citation

  • Ivan S. Maksymov, 2024. "Quantum Mechanics of Human Perception, Behaviour and Decision-Making: A Do-It-Yourself Model Kit for Modelling Optical Illusions and Opinion Formation in Social Networks," Papers 2404.10554, arXiv.org.
  • Handle: RePEc:arx:papers:2404.10554
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2404.10554
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Katarzyna Sznajd-Weron & Józef Sznajd, 2000. "Opinion Evolution In Closed Community," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1157-1165.
    2. Daron Acemoğlu & Giacomo Como & Fabio Fagnani & Asuman Ozdaglar, 2013. "Opinion Fluctuations and Disagreement in Social Networks," Mathematics of Operations Research, INFORMS, vol. 38(1), pages 1-27, February.
    3. Chen, Ruyin & Xiong, Yue & Zhuge, Shengying & Li, Zekun & Chen, Qitie & He, Zhifen & Wu, Dingqiang & Hou, Fang & Zhou, Jiawei, 2023. "Regulation and prediction of multistable perception alternation," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    4. Mengxing Wei & Ali al-Nowaihi & Sanjit Dhami, 2019. "Quantum Decision Theory, Bounded Rationality and the Ellsberg Paradox," Studies in Microeconomics, , vol. 7(1), pages 110-139, June.
    5. repec:nas:journl:v:115:y:2018:p:9216-9221 is not listed on IDEAS
    6. Galam, Serge, 1997. "Rational group decision making: A random field Ising model at T = 0," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 238(1), pages 66-80.
    7. Solveiga Stonkute & Jochen Braun & Alexander Pastukhov, 2012. "The Role of Attention in Ambiguous Reversals of Structure-From-Motion," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-12, May.
    8. Xi Chen & Panayiotis Tsaparas & Jefrey Lijffijt & Tijl De Bie, 2021. "Opinion dynamics with backfire effect and biased assimilation," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-17, September.
    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. Catherine A. Glass & David H. Glass, 2021. "Social Influence of Competing Groups and Leaders in Opinion Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 799-823, October.
    2. Piotr Przybyła & Katarzyna Sznajd-Weron & Rafał Weron, 2014. "Diffusion Of Innovation Within An Agent-Based Model: Spinsons, Independence And Advertising," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-22.
    3. repec:hal:wpaper:hal-00623966 is not listed on IDEAS
    4. Tiwari, Mukesh & Yang, Xiguang & Sen, Surajit, 2021. "Modeling the nonlinear effects of opinion kinematics in elections: A simple Ising model with random field based study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    5. Katarzyna Ostasiewicz & Michal H. Tyc & Piotr Goliczewski & Piotr Magnuszewski & Andrzej Radosz & Jan Sendzimir, 2006. "Integrating economic and psychological insights in binary choice models with social interactions," Papers physics/0609170, arXiv.org.
    6. AskariSichani, Omid & Jalili, Mahdi, 2015. "Influence maximization of informed agents in social networks," Applied Mathematics and Computation, Elsevier, vol. 254(C), pages 229-239.
    7. Shane T. Mueller & Yin-Yin Sarah Tan, 2018. "Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization," Journal of Computational Social Science, Springer, vol. 1(1), pages 15-48, January.
    8. Castro, Luis E. & Shaikh, Nazrul I., 2018. "A particle-learning-based approach to estimate the influence matrix of online social networks," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 1-18.
    9. Juliette Rouchier & Emily Tanimura, 2012. "When overconfident agents slow down collective learning," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00623966, HAL.
    10. Matjaž Steinbacher & Mitja Steinbacher, 2019. "Opinion Formation with Imperfect Agents as an Evolutionary Process," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 479-505, February.
    11. Schweitzer, Frank & Zimmermann, Jörg & Mühlenbein, Heinz, 2002. "Coordination of decisions in a spatial agent model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 303(1), pages 189-216.
    12. Juliette Rouchier & Emily Tanimura, 2012. "When overconfident agents slow down collective learning," Post-Print hal-00623966, HAL.
    13. Elizabeth L. Ogburn & Ilya Shpitser & Youjin Lee, 2020. "Causal inference, social networks and chain graphs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1659-1676, October.
    14. Gualandi, Stefano & Toscani, Giuseppe, 2019. "Size distribution of cities: A kinetic explanation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 221-234.
    15. Andrés Chacoma & Damián H Zanette, 2015. "Opinion Formation by Social Influence: From Experiments to Modeling," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-16, October.
    16. Oliveira, Igor V.G. & Wang, Chao & Dong, Gaogao & Du, Ruijin & Fiore, Carlos E. & Vilela, André L.M. & Stanley, H. Eugene, 2024. "Entropy production on cooperative opinion dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    17. Domino, Krzysztof & Miszczak, Jarosław Adam, 2022. "Will you infect me with your opinion?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    18. Galam, Serge, 2011. "Collective beliefs versus individual inflexibility: The unavoidable biases of a public debate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(17), pages 3036-3054.
    19. Pawel Sobkowicz, 2009. "Modelling Opinion Formation with Physics Tools: Call for Closer Link with Reality," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-11.
    20. Fang Wu & Bernardo A. Huberman, 2004. "Social Structure and Opinion Formation," Computational Economics 0407002, University Library of Munich, Germany.
    21. Braha, Dan & de Aguiar, Marcus A. M., 2018. "Voting contagion: Modeling and analysis of a century of U.S. presidential elections," SocArXiv mzxnr, Center for Open Science.

    More about this item

    Statistics

    Access and download statistics

    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:arx:papers:2404.10554. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.