Skip to main content

A Group Decision Making Method for Integrating Outcome Preferences in Hypergame Situations

  • Conference paper
Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

Included in the following conference series:

Abstract

This paper presents a novel group decision making method for integrating outcome preferences in the first-level hypergame models where each player correctly perceives the strategy set, but perceives possibly different outcome preferences of the opponent players. To get more correct preferences information in hypergame models, each player is often consisted of a group of decision makers who can give their perception about opponent players’ preferences respectively. In the face of opponent players’ different linguistic preferences relations over outcome space perceived by different decision makers, a group fuzzy preferences relation is first accurately computed using standard fuzzy arithmetic operations. Concept of consensus winner is then introduced to decide the crisp outcome preference vectors. A numerical example is provided at the end to illustrate the method.

This work is supported by National Natural Science Foundation of China Grant #70471031.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wang, M., Hipel, K.W., Frase, N.M.: Solution concepts in hypergames. Applied Mathematics and Computation 34, 147–171 (1989)

    Article  MATH  MathSciNet  Google Scholar 

  2. Putro, U.S., Kijima, K., Takahashi, S.: Adaptive learning of hypergame situations using a genetic algorithm. IEEE Transactions on Systems, Man and Cybernetics-Part A: Systems and Humans 5, 562–572 (2000)

    Article  Google Scholar 

  3. Hipel, K.W., Wang, M., Frase, N.M.: Hypergame analysis of the Falkland Island crisis. Internat. Stud. Quart. 32, 335–358 (1988)

    Article  Google Scholar 

  4. Hipel, K.W., Dagnino, A., Frase, N.M.: A hypergame algorithm for modeling misperceptions in bargaining. J. Environmental Management 12, 131–152 (1988)

    Google Scholar 

  5. Herrera, F., Herrera-Viedma, E., Verdegay, J.L.: A rational consensus model in group decision making using linguistic assessments. Fuzzy Sets and Systems 88, 31–49 (1997)

    Article  Google Scholar 

  6. Dubois, D., Prade, H.: Ranking of fuzzy numbers in the setting of possibility theory. Inform. Sci. 30, 183–224 (1983)

    Article  MATH  MathSciNet  Google Scholar 

  7. Buckley, J.J.: Ranking alternatives using fuzzy numbers. Fuzzy Sets and Systems 15, 21–31 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  8. Kacprzyk, J., Fedrizzi, M., Nurmi, H.: Group decision making and consensus under fuzzy preferences and fuzzy majority. Fuzzy Sets and Systems 49, 21–31 (1992)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Song, Y., Wang, Q., Li, Z. (2005). A Group Decision Making Method for Integrating Outcome Preferences in Hypergame Situations. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_84

Download citation

  • DOI: https://doi.org/10.1007/11539506_84

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics