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An Objective Function Based on Fuzzy Preferences in Dynamic Decision Making

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3214))

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Abstract

This paper presents a mathematical model for dynamic decision making with an objective function induced from fuzzy preferences. The fuzzy preference is related to decision making in artificial intelligence, and this paper models human behavior based on his fuzzy preferences. A reasonable criterion based on fuzzy preferences is formulated for the dynamic decision making, and an optimality equation for this model is derived by dynamic programming.

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References

  1. Coubon, J.-C., Dubois, D., Roy, B.: Autour de l’aide à la décision et de l’intelligence artificielle. Rapport LAFORIA/IBP 94/01 (1994)

    Google Scholar 

  2. Fishburn, P.C.: Utility Theory for Decision Making. John Wiley and Sons, New York (1970)

    MATH  Google Scholar 

  3. Fodor, J., Roubens, M.: Fuzzy Preference Modelling and Multi-Criteria Decision Support. Kluwer Academic Publishers, Dordrecht (1994)

    Google Scholar 

  4. Ishibuchi, H., Tanaka, H.: Fuzzy regression analysis using neural networks. Fuzzy Sets and Systems 50, 257–265 (1992)

    Article  MathSciNet  Google Scholar 

  5. Kaminka, G.A., Lima, P.U., Rojas, R. (eds.): RoboCup 2002. LNCS (LNAI), vol. 2752. Springer, Heidelberg (2003)

    MATH  Google Scholar 

  6. Klir, G.J., Yuan, B.: Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice-Hall, London (1995)

    MATH  Google Scholar 

  7. von Neumann, J., Morgenstern, O.: Theory of Games and Economic Behavior. Princeton University Press, Princeton (1944)

    MATH  Google Scholar 

  8. Newell, A., Simon, H.A.: Human Problems Solving. Prentice-Hall, Englewood Cliffs (1972)

    Google Scholar 

  9. Pomerol, J.-C.: Artificial intelligence and human decision making. European Journal of Operational Research 99, 3–25 (1997)

    Article  MATH  Google Scholar 

  10. Puri, M.L., Ralescu, D.: The concept of normality for fuzzy random variables. Ann. Prob. 13, 1373–1379 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  11. Simon, H.A.: The New Science of Management Decision. Prentice-Hall, Englewood Cliffs (1963)

    Google Scholar 

  12. Simon, H.A.: The Sciences of the Artificial. MIT Press, Cambridge (1969)

    Google Scholar 

  13. Slotine, J.J.E., Li, W.: Applied Nonlinear Control. Prentice-Hall, Englewood Cliffs (1991)

    MATH  Google Scholar 

  14. Yoshida, Y.: Continuous-time fuzzy decision processes with discounted rewards. Fuzzy Sets and Systems 139, 33–348 (2003)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Faculty of Economics and Business Administration, the University of Kitakyushu, 4-2-1 Kitagata, Kokuraminami, Kitakyushu, 802-8577, Japan

    Yuji Yoshida & Satoru Kumamoto

  2. Faculty of Science, Chiba University, 1-33 Yayoi-cho, Inage, Chiba, 263-8522, Japan

    Masami Yasuda & Jun-ichi Nakagami

  3. Faculty of Education, Chiba University, 1-33 Yayoi-cho, Inage, Chiba, 263-8522, Japan

    Masami Kurano

Authors
  1. Yuji Yoshida
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  2. Masami Yasuda
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  3. Jun-ichi Nakagami
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  4. Masami Kurano
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  5. Satoru Kumamoto
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Editor information

Editors and Affiliations

  1. KES International, 2nd Floor, 145-157 St John Street, EC1V 4PY, London, United Kingdom

    Mircea Gh. Negoita

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, BN2 4GJ, Moulsecoomb, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2004 Springer-Verlag Berlin Heidelberg

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Yoshida, Y., Yasuda, M., Nakagami, Ji., Kurano, M., Kumamoto, S. (2004). An Objective Function Based on Fuzzy Preferences in Dynamic Decision Making. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30133-2_164

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  • DOI: https://doi.org/10.1007/978-3-540-30133-2_164

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23206-3

  • Online ISBN: 978-3-540-30133-2

  • eBook Packages: Springer Book Archive

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