IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v347y2019icp417-428.html
   My bibliography  Save this article

Uncertainty measurement with belief entropy on the interference effect in the quantum-like Bayesian Networks

Author

Listed:
  • Huang, Zhiming
  • Yang, Lin
  • Jiang, Wen

Abstract

The Bayesian Network is a kind of probabilistic graphical models, having been applied to various fields for inference and learning. A quantum-like Bayesian Network has been proposed to model the Prisoner’s dilemma, the famous example of Social Dilemma games. Recent findings reveal that people’s behaviors violate the Sure Thing Principle in such games. The quantum-like Bayesian Network considers the people’s behaviors as wave functions and explains the violation as the interference effect. The determination of the interference effect is an essential part of modeling the Bayesian Network.

Suggested Citation

  • Huang, Zhiming & Yang, Lin & Jiang, Wen, 2019. "Uncertainty measurement with belief entropy on the interference effect in the quantum-like Bayesian Networks," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 417-428.
    • Handle: RePEc:eee:apmaco:v:347:y:2019:i:c:p:417-428
    DOI: 10.1016/j.amc.2018.11.036
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300318310105
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2018.11.036?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. Shaikh, Pervez Hameed & Nor, Nursyarizal Bin Mohd & Nallagownden, Perumal & Elamvazuthi, Irraivan & Ibrahim, Taib, 2014. "A review on optimized control systems for building energy and comfort management of smart sustainable buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 409-429.
    2. V. Yukalov & D. Sornette, 2011. "Decision theory with prospect interference and entanglement," Theory and Decision, Springer, vol. 70(3), pages 283-328, March.
    3. Vyacheslav I. Yukalov & Didier Sornette, 2010. "Mathematical Structure Of Quantum Decision Theory," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 13(05), pages 659-698.
    4. Fei, Liguo & Zhang, Qi & Deng, Yong, 2018. "Identifying influential nodes in complex networks based on the inverse-square law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1044-1059.
    5. Daniel Ellsberg, 1963. "Risk, Ambiguity, and the Savage Axioms: Reply," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 77(2), pages 336-342.
    6. Rong Zhang & Baabak Ashuri & Yong Deng, 2017. "A novel method for forecasting time series based on fuzzy logic and visibility graph," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(4), pages 759-783, December.
    7. Yin, Likang & Deng, Yong, 2018. "Measuring transferring similarity via local information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 498(C), pages 102-115.
    8. Borunda, Mónica & Jaramillo, O.A. & Reyes, Alberto & Ibargüengoytia, Pablo H., 2016. "Bayesian networks in renewable energy systems: A bibliographical survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 32-45.
    9. Gambelli, Danilo & Alberti, Francesca & Solfanelli, Francesco & Vairo, Daniela & Zanoli, Raffaele, 2017. "Third generation algae biofuels in Italy by 2030: A scenario analysis using Bayesian networks," Energy Policy, Elsevier, vol. 103(C), pages 165-178.
    10. Xinyi Zhou & Yong Hu & Yong Deng & Felix T. S. Chan & Alessio Ishizaka, 2018. "A DEMATEL-based completion method for incomplete pairwise comparison matrix in AHP," Annals of Operations Research, Springer, vol. 271(2), pages 1045-1066, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cui, Huizi & Zhou, Lingge & Li, Yan & Kang, Bingyi, 2022. "Belief entropy-of-entropy and its application in the cardiac interbeat interval time series analysis," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    2. Wen Jiang & Zeyu Ma & Xinyang Deng, 2019. "An attack-defense game based reliability analysis approach for wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(4), pages 15501477198, April.
    3. Jingmei Xiao & Mei Cai & Yu Gao, 2022. "A VIKOR-Based Linguistic Multi-Attribute Group Decision-Making Model in a Quantum Decision Scenario," Mathematics, MDPI, vol. 10(13), pages 1-23, June.
    4. Xue, Yige & Deng, Yong, 2022. "A decomposable Deng entropy," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    5. Wen, Tao & Jiang, Wen, 2019. "Identifying influential nodes based on fuzzy local dimension in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 332-342.
    6. Liguo Fei & Jun Xia & Yuqiang Feng & Luning Liu, 2019. "A novel method to determine basic probability assignment in Dempster–Shafer theory and its application in multi-sensor information fusion," International Journal of Distributed Sensor Networks, , vol. 15(7), pages 15501477198, July.

    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. Li, Meizhu & Zhang, Qi & Deng, Yong, 2018. "Evidential identification of influential nodes in network of networks," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 283-296.
    2. Yin, Likang & Deng, Yong, 2018. "Toward uncertainty of weighted networks: An entropy-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 176-186.
    3. Fei, Liguo & Zhang, Qi & Deng, Yong, 2018. "Identifying influential nodes in complex networks based on the inverse-square law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1044-1059.
    4. Wei, Bo & Deng, Yong, 2019. "A cluster-growing dimension of complex networks: From the view of node closeness centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 80-87.
    5. Ismaël Rafaï & Sébastien Duchêne & Eric Guerci & Irina Basieva & Andrei Khrennikov, 2022. "The triple-store experiment: a first simultaneous test of classical and quantum probabilities in choice over menus," Theory and Decision, Springer, vol. 92(2), pages 387-406, March.
    6. Fellnhofer, Katharina & Sornette, Didier, 2022. "Embracing The Intuitive-Analytical Paradox? How Intuitive And Analytical Decision-Making Drive Paradoxes In Simple And Complex Environments," OSF Preprints evjd6, Center for Open Science.
    7. Thomas Boyer-Kassem & Sébastien Duchêne & Eric Guerci, 2016. "Quantum-like models cannot account for the conjunction fallacy," Theory and Decision, Springer, vol. 81(4), pages 479-510, November.
    8. Eichberger, Jürgen & Pirner, Hans Jürgen, 2018. "Decision theory with a state of mind represented by an element of a Hilbert space: The Ellsberg paradox," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 131-141.
    9. Godfrey Cadogan, 2012. "Representation theory for risk on markowitz-tversky-kahneman topology," Economics Bulletin, AccessEcon, vol. 32(4), pages 1-34.
    10. Xu, Paiheng & Zhang, Rong & Deng, Yong, 2018. "A novel visibility graph transformation of time series into weighted networks," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 201-208.
    11. Ashtiani, Mehrdad & Azgomi, Mohammad Abdollahi, 2015. "A survey of quantum-like approaches to decision making and cognition," Mathematical Social Sciences, Elsevier, vol. 75(C), pages 49-80.
    12. Small, Mitchell J. & Wong-Parodi, Gabrielle & Kefford, Benjamin M. & Stringer, Martin & Schmeda-Lopez, Diego R. & Greig, Chris & Ballinger, Benjamin & Wilson, Stephen & Smart, Simon, 2019. "Generating linked technology-socioeconomic scenarios for emerging energy transitions," Applied Energy, Elsevier, vol. 239(C), pages 1402-1423.
    13. Wen, Tao & Jiang, Wen, 2018. "An information dimension of weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 388-399.
    14. Maroussia Favre & Didier Sornette, 2015. "A Generic Model of Dyadic Social Relationships," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-16, March.
    15. Maroussia Favre & Amrei Wittwer & Hans Rudolf Heinimann & Vyacheslav I Yukalov & Didier Sornette, 2016. "Quantum Decision Theory in Simple Risky Choices," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-29, December.
    16. Wen Jiang & Zeyu Ma & Xinyang Deng, 2019. "An attack-defense game based reliability analysis approach for wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(4), pages 15501477198, April.
    17. Ferro, Giuseppe M. & Kovalenko, Tatyana & Sornette, Didier, 2021. "Quantum decision theory augments rank-dependent expected utility and Cumulative Prospect Theory," Journal of Economic Psychology, Elsevier, vol. 86(C).
    18. Wang, Xiaojie & Slamu, Wushour & Guo, Wenqiang & Wang, Sixiu & Ren, Yan, 2022. "A novel semi local measure of identifying influential nodes in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    19. Dong-Rui Chen & Chuang Liu & Yi-Cheng Zhang & Zi-Ke Zhang, 2019. "Predicting Financial Extremes Based on Weighted Visual Graph of Major Stock Indices," Complexity, Hindawi, vol. 2019, pages 1-17, October.
    20. Kargbo, Hannah & Harris, Jonathan Stuart & Phan, Anh N., 2021. "“Drop-in” fuel production from biomass: Critical review on techno-economic feasibility and sustainability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).

    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:apmaco:v:347:y:2019:i:c:p:417-428. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.