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Stable strategies analysis based on the utility of Z-number in the evolutionary games

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  • Kang, Bingyi
  • Chhipi-Shrestha, Gyan
  • Deng, Yong
  • Hewage, Kasun
  • Sadiq, Rehan

Abstract

Evolutionary games with the fuzzy set are attracting growing interest. While among previous studies, the role of the reliability of knowledge in such an infrastructure is still virgin and may become a fascinating issue. Z-number is combined with “restriction” and “reliability”, which is an efficient framework to simulate the thinking of human. In this paper, the stable strategies analysis based on the utility of Z-number in the evolutionary games is proposed, which can simulate the procedure of human’s competition and cooperation more authentically and more flexibly. Some numerical examples and an application are used to illustrate the effectiveness of the proposed methodology. Results show that total utility of Z-number can be used as an index to extend the classical evolutionary games into ones linguistic-based, which is applicable in the real applications since the payoff matrix is always determined by the knowledge of human using uncertain information, e.g., (outcome of the next year, about fifty thousand dollars, likely).

Suggested Citation

  • Kang, Bingyi & Chhipi-Shrestha, Gyan & Deng, Yong & Hewage, Kasun & Sadiq, Rehan, 2018. "Stable strategies analysis based on the utility of Z-number in the evolutionary games," Applied Mathematics and Computation, Elsevier, vol. 324(C), pages 202-217.
    • Handle: RePEc:eee:apmaco:v:324:y:2018:i:c:p:202-217
    DOI: 10.1016/j.amc.2017.12.006
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    References listed on IDEAS

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    1. Hammerstein, Peter & Leimar, Olof, 2015. "Evolutionary Game Theory in Biology," Handbook of Game Theory with Economic Applications,, Elsevier.
    2. 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.
    3. Samira Keivanpour & Daoud Ait-Kadi & Christian Mascle, 2017. "Automobile manufacturers’ strategic choice in applying green practices: joint application of evolutionary game theory and fuzzy rule-based approach," International Journal of Production Research, Taylor & Francis Journals, vol. 55(5), pages 1312-1335, March.
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    Cited by:

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    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.
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    5. 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.
    6. 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.
    7. Dong, Yukun & Xu, Hedong & Fan, Suohai, 2019. "Memory-based stag hunt game on regular lattices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 247-255.
    8. Deng, Xinyang & Jiang, Wen & Wang, Zhen, 2020. "An Information Source Selection Model Based on Evolutionary Game Theory," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    9. Bowen Qin & Fuyuan Xiao, 2019. "An improved method to determine basic probability assignment with interval number and its application in classification," International Journal of Distributed Sensor Networks, , vol. 15(1), pages 15501477188, January.
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    12. Sun, Qingqing & Chen, Hong & Long, Ruyin & Yang, Jiahui, 2023. "Who will pay for the “bicycle cemetery”? Evolutionary game analysis of recycling abandoned shared bicycles under dynamic reward and punishment," European Journal of Operational Research, Elsevier, vol. 305(2), pages 917-929.

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