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Group Decision Support Using Fuzzy Cognitive Maps for Causal Reasoning

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Abstract

Cognitive maps have been used for analysing and aiding decision-making by investigating causal links among relevant domain concepts. A fuzzy cognitive map (FCM) is an extension of a cognitive map with the additional capability of representing feedback through weighted causal links. FCMs can be used as tools for both static as well as dynamic analysis of scenarios evolving with time. An FCM represents an expert's domain knowledge in a form that lends itself to relatively easy integration into a collective knowledge base for a group involved in a decision process. The resulting group FCM has the potential to serve as a useful tool in a group decision support environment. An appropriate methodology for the development and analysis of group FCMs is required. A framework for such a methodology consisting of the development and application phases is presented.

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References

  • Axelrod, R. (1976). Structure of Decision. Princeton, USA: Princeton University Press.

    Google Scholar 

  • Caudill, M. (1990). “Using Neural Nets: Fuzzy Cognitive Maps”, AI Expert, 49–53.

  • Eden, C. (1999). Strategic Thinking with Computers, Long Range Planning, Vol. 23, No. 6, 35–43.

    Google Scholar 

  • Eden, C. and F. Ackerman. (1998). Making Strategy: The Journey of Strategic Management. London, UK: SAGE Publications.

    Google Scholar 

  • Elert, G. (1999). The Chaos Hypertexbook, http://hypertextbook.com/chaos/about.shtml (accessed on August 7, 2002).

  • Forrester, J. W. (1968). Principles of Systems. MA, USA: Wright Allen Press.

    Google Scholar 

  • Hagiwara, M. (1992). “Extended Fuzzy Cognitive Maps,” Proceedings of the 1st IEEE International Conference on Fuzzy Systems,New York, NY, 795–801.

  • Kardaras, D. and B. Karakostas. (1999). “The Use of Fuzzy Cognitive Maps to Simulate Information Systems Strategic Planning Process,” Information and Software Technology 41 (4), 197–210.

    Google Scholar 

  • Kosko, B. (1986). “Fuzzy Cognitive Maps,” International Journal of Man-Machine Studies 24, 65–75.

    Google Scholar 

  • Kosko, B. (1987). “Fuzzy Associative Memory,” in A. Kandel (Ed.), Fuzzy Expert Systems. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Kosko, B. (1988). “Hidden Patterns in Combined and Adaptive Knowledge Networks,” International Journal of Approximate Reasoning 2, 377–393.

    Google Scholar 

  • Lee, S. and I. Han. (2000). “Fuzzy Cognitive Map for the Design of EDI Controls,” Information and Management 37, 37–50.

    Google Scholar 

  • Lee, K., S. Kim, and M. Sakawa. (1996). “On-Line Fault Diagnosis by Using Fuzzy Cognitive Map,” IEICE Transactions of Fundamentals E79-A(6), 921–927.

    Google Scholar 

  • Lee, K. C. and H. S. Kim. (1997). “A Fuzzy Cognitive Map-Based Bi-Directional Inference Mechanism: An Application to Stock Investment Analysis,” Intelligent Systems in Accounting, Finance & Management 6, 41–57.

    Google Scholar 

  • Lee, K. C., W. J. Lee, O. B. Kwon, J. H. Han, and P. I. Yu. (1998). “Strategic Planning Simulation Based on Fuzzy Cognitive Map Knowledge and Differential Game,” Simulation 316–327.

  • Park, K. S. (1995). “Fuzzy Cognitive Maps Considering Time Relationships,” International Journal of Human-Computer Studies 157–167.

  • Saaty, T. L. (1980). The Analytic Hierarchy Process.New York: McGraw-Hill.

    Google Scholar 

  • School of Information Technology. (2003). The Virtual World Mapper (VWM) User and Technical Manuals. Perth: Murdoch University.

    Google Scholar 

  • Taber, W. R. and M. A. Siegel. (1987). “Estimation of Expert Weights Using Fuzzy Cognitive Maps,” Proceedings of the IEEE International Conference on Neural Networks, San Diego, Vol. II, 319–325.

    Google Scholar 

  • Tsadiras, A. K. and K. G. Margaritis. (1994). “On Transition and Convergence Properties of Extended Fuzzy Cognitive Maps,” Proceedings of the 2nd Hellenic European Conference on Mathematics and Informatics (HERMIS'94), Athens.

  • Tsadiras, A. K. and K. G. Margaritis. (1995a). “Using Fuzzy Cognitive Maps for Decision Making,” Proceedings of the 3rd Balkan Conference on Operations Research, 1–14.

  • Tsadiras, A. K. and K. G. Margaritis. (1995b). “Strategic Planning Using Extended Fuzzy Cognitive Maps,” Studies in Informatics and Control 4 (3), 237–245.

    Google Scholar 

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Authors and Affiliations

  1. School of Information Technology, Murdoch University, Perth, WA 6150, Australia.

    M. Shamim Khan

  2. Graduate School of Business, Curtin University of Technology, GPO Box U 1987, Perth, WA, 6845, Australia.

    Mohammed Quaddus

Authors
  1. M. Shamim Khan
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  2. Mohammed Quaddus
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Khan, M.S., Quaddus, M. Group Decision Support Using Fuzzy Cognitive Maps for Causal Reasoning. Group Decision and Negotiation 13, 463–480 (2004). https://doi.org/10.1023/B:GRUP.0000045748.89201.f3

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