IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v366y2020ics0096300319306769.html
   My bibliography  Save this article

Multi-UAV counter-game model based on uncertain information

Author

Listed:
  • Xu, Jiwei
  • Deng, Zhenghong
  • Song, Qun
  • Chi, Qian
  • Wu, Tao
  • Huang, Yijie
  • Liu, Dan
  • Gao, Mingyu

Abstract

When a multi-UAV is performing a mission, the information obtained by the commander could be highly uncertain. How to choose strategies based on uncertain information will directly affect the success or failure of the UAV mission. In this paper, we present a multi-UAV confrontation model based on uncertain information, which can provide a powerful reference for strategy selection. We established a multi-UAV game model, and proposed a game payment function, and introduce a situation matrix to imitate the uncertainty of war information. In order to complete the calculation of uncertain information, the paper introduces a complex calculation method and establishes an interval decision model. The simulated experiment results show that the situation matrix proposed in this paper could represents the uncertainty in the battle field, and the interval decision method could process data effectively. Furthermore, the proposed algorithm could provide optimal strategy for decision support in battle field with uncertain information, and provide new research direction for game with uncertain information.

Suggested Citation

  • Xu, Jiwei & Deng, Zhenghong & Song, Qun & Chi, Qian & Wu, Tao & Huang, Yijie & Liu, Dan & Gao, Mingyu, 2020. "Multi-UAV counter-game model based on uncertain information," Applied Mathematics and Computation, Elsevier, vol. 366(C).
    • Handle: RePEc:eee:apmaco:v:366:y:2020:i:c:s0096300319306769
    DOI: 10.1016/j.amc.2019.124684
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300319306769
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2019.124684?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. Liu, Jinzhuo & Meng, Haoran & Wang, Wei & Xie, Zhongwen & Yu, Qian, 2019. "Evolution of cooperation on independent networks: The influence of asymmetric information sharing updating mechanism," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 234-241.
    2. Corrado, Charles J & Jordan, Bradford D, 1997. "Risk Aversion, Uncertain Information, and Market Efficiency," Review of Quantitative Finance and Accounting, Springer, vol. 8(1), pages 51-68, January.
    3. Xu, Jiwei & Deng, Zhenghong & Gao, Bo & Song, Qun & Tian, Zhihong & Wang, Qiuling & Gao, Mingyu & Niu, Zhenxi, 2019. "Popularity-driven strategy updating rule promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 353(C), pages 82-87.
    4. Chu, Chen & Zhai, Yao & Mu, Chunjiang & Hu, Die & Li, Tong & Shi, Lei, 2019. "Reputation-based popularity promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    5. Zhu, Peican & Wang, Xinyu & Li, Shudong & Guo, Yangming & Wang, Zhen, 2019. "Investigation of epidemic spreading process on multiplex networks by incorporating fatal properties," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 512-524.
    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. Wang, Zi-Ren & Deng, Zheng-Hong & Wang, Huan-Bo & Li, HuXiong & X, Fei-Wang, 2022. "Uneven Resources network promotes cooperation in the prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    2. Wang, Qiuling & Du, Chunpeng, 2019. "Impact of expansion of priority range on cooperation in the prisoner's dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 129(C), pages 77-80.
    3. Pan, Qiuhui & Wang, Linpeng & He, Mingfeng, 2020. "Social dilemma based on reputation and successive behavior," Applied Mathematics and Computation, Elsevier, vol. 384(C).
    4. Zhang, Zaisheng & Song, Fang & Song, Zongbin, 2020. "Promoting knowledge sharing in the workplace: Punishment v. reward," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    5. Han, Weiwei & Zhang, Zhipeng & Sun, Junqing & Xia, Chengyi, 2022. "Role of reputation constraints in the spatial public goods game with second-order reputation evaluation," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    6. Liao, Hui-Min & Hao, Qing-Yi & Qian, Jia-Li & Wu, Chao-Yun & Guo, Ning & Ling, Xiang, 2023. "Cooperative evolution under the joint influence of local popularity and global popularity," Applied Mathematics and Computation, Elsevier, vol. 439(C).
    7. Li, Shulan & Hong, Lijun & Geng, Yini & Shen, Chen, 2020. "Popularity-driven fitness calculation promotes cooperation in spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    8. Wang, Zi-Ren & Deng, Zheng-Hong & Wang, Huan-Bo & Qu, Yun, 2021. "Moderate irrational sentiment-driven fitness can promote cooperation in the prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    9. Zhu, Peican & Wang, Xiaoyu & Jia, Danyang & Guo, Yangming & Li, Shudong & Chu, Chen, 2020. "Investigating the co-evolution of node reputation and edge-strategy in prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    10. Zhang, Lan & Xie, Yuan & Huang, Changwei & Li, Haihong & Dai, Qionglin, 2020. "Heterogeneous investments induced by historical payoffs promote cooperation in spatial public goods games," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    11. Zhang, Liming & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2022. "Migration based on environment comparison promotes cooperation in evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    12. Wang, Jin-Shan & Wu, Yong-Ping & Li, Li & Sun, Gui-Quan, 2020. "Effect of mobility and predator switching on the dynamical behavior of a predator-prey model," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    13. Yunsheng Deng & Jihui Zhang, 2022. "The choice-decision based on memory and payoff favors cooperation in stag hunt game on interdependent networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(2), pages 1-13, February.
    14. Chun-Teck Lye & Tuan-Hock Ng & Kwee-Pheng Lim & Chin-Yee Gan, 2020. "Investor protection and market reaction to unusual market activity replies," International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 16(8), pages 2034-2069, July.
    15. Wu, Jiang & Zuo, Renxian & He, Chaocheng & Xiong, Hang & Zhao, Kang & Hu, Zhongyi, 2022. "The effect of information literacy heterogeneity on epidemic spreading in information and epidemic coupled multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    16. Quan, Ji & Cui, Shihui & Chen, Wenman & Wang, Xianjia, 2023. "Reputation-based probabilistic punishment on the evolution of cooperation in the spatial public goods game," Applied Mathematics and Computation, Elsevier, vol. 441(C).
    17. Piccoli, Pedro & Chaudhury, Mo & Souza, Alceu, 2017. "How do stocks react to extreme market events? Evidence from Brazil," Research in International Business and Finance, Elsevier, vol. 42(C), pages 275-284.
    18. Gagan Matta, 2020. "Science communication as a preventative tool in the COVID19 pandemic," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-14, December.
    19. Sturm, Philipp, 2013. "Operational and reputational risk in the European banking industry: The market reaction to operational risk events," Journal of Economic Behavior & Organization, Elsevier, vol. 85(C), pages 191-206.
    20. Zhou, Baoquan & Han, Bingtao & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed, 2021. "Ergodic stationary distribution and extinction of a hybrid stochastic SEQIHR epidemic model with media coverage, quarantine strategies and pre-existing immunity under discrete Markov switching," Applied Mathematics and Computation, Elsevier, vol. 410(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:366:y:2020:i:c:s0096300319306769. 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.