• DocumentCode
    2375138
  • Title

    A hybrid method for effective management of the uncertainty in army decision making using cognitive agents and Classification based on Fuzzy Association Rules

  • Author

    Heravi, Mojtaba ; Akramizadeh, Ali ; Pourakbar, Mohammadreza ; Menhaj, M.B.

  • Author_Institution
    Cognitive Sci. & Artificial Intell. Lab., Inst. for Biol. Sci., Tehran, Iran
  • fYear
    2013
  • fDate
    27-29 Aug. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Decision making is an important problem in most of the army operations. One of the challenging issues in this area is uncertainty in wars with uncertain information which causes many destructive effects on the results of strategies in battlefields. Cognitive Agent (CA) brings about an improvement by reducing the uncertainties meanwhile causes some unavoidable negative effects in critical decisions. Classification based on Fuzzy Association Rules (CFAR) is an effective method for rule mining which has the ability to deal with Sharp Boundary problems due to its flexibility in quantitative attribute domains and therefore it reduces the uncertainty. In this article a new hybrid method is proposed to reduce the uncertainty in decision making based on CA and CFAR. Simulation results show that the proposed method provides more understandable and has lower risk and more precise and flexibility as it reduces the generated rules.
  • Keywords
    data mining; decision making; decision support systems; fuzzy set theory; military computing; multi-agent systems; pattern classification; CA; CFAR method; army decision making; classification based on fuzzy association rules; cognitive agents; quantitative attribute domains; rule mining; sharp boundary problems; uncertainty management; Asymmetric Warfare; Classification based on Fuzzy Association Rules; Cognitive Agent; Decision Making; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (IFSC), 2013 13th Iranian Conference on
  • Conference_Location
    Qazvin
  • Print_ISBN
    978-1-4799-1227-8
  • Type

    conf

  • DOI
    10.1109/IFSC.2013.6675655
  • Filename
    6675655