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Combine the Objective Features with the Subjective Feelings in Personal Multi-alternative Decision Making Modeling

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5819))

Abstract

Abstract. In this paper we propose a computer modeling framework for personal multi-alternative decision making. It integrates both the objective feature space searching and evaluation and subjective feeling space deliberating and evaluation process. A case study on fashion decision making is given out as an example. It shows that the proposed model outperforms the currently widely studied ones in terms of prediction accuracy due to the consideration of the stochastic characteristics and the psychological effects that occur quite often in human multi-alternative decision making.

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References

  1. Doyle, J.: Prospects for the Preferences. Computational Intelligence 20(2), 111–136 (2004)

    Article  MathSciNet  Google Scholar 

  2. Holand, J.: Adaptation in Natural and Artificial Systems. In: An Introductory Analysis with Applications to Biology,Control and Artificial Intelligence. University of Michigan Press, Ann Harbor (1975)

    Google Scholar 

  3. Dorigo, M.: Ant colony system-a cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation 1(1), 53–66 (1997)

    Article  Google Scholar 

  4. Von Neumann, J.: Theory of games and economic behavior. Princeton University Press, Princeton (1947)

    MATH  Google Scholar 

  5. Janis, I.L., Mann, L.: Decision making: a psychological analysis of conflict, chlice and commitment. Free Press, New York (1977)

    Google Scholar 

  6. Kahneman, D., Tversky, A.: Prospect theory: an analysis of decision under risk. Econometrica 47, 263–291 (1979)

    Article  MATH  Google Scholar 

  7. Machina, M.J.: Expected Utility analysis without the independence axiom. Econometrica, 277–323 (1982)

    Google Scholar 

  8. Wakker, P.P.: Additive representations of preferences. Kluwer Academic Publishers, Dordrecht (1989a)

    Book  MATH  Google Scholar 

  9. Busemeyer, J.R., Townsend, J.T.: Decision Field Theory: A dynamic-cognitive aproach to decision making in an uncertain environment. Psychological Review 100(3), 432–459 (1993)

    Article  Google Scholar 

  10. Simon, T.W., Schuttet, J.E., Axelsson, J.R.C., Mitsuo, N.: Concept, methods and tools in Sensory Engineering. Theoretical Issues in Ergonomics Science (5), 214–231 (2004)

    Google Scholar 

  11. Roe, R., Busemeyer, J.R., Townsend, J.T.: Multi-alternative decision filed theory:A dynamic connectionist model of decision making. Psychology Review 108, 370–392 (2001)

    Article  Google Scholar 

  12. Nakanishi, Y.: Capturing preference into a function using interactions with a manual evolutionary design aid system. Genetic Programming, 133–138 (1996)

    Google Scholar 

  13. Lee, J.-Y., Cho, S.-B.: Interactive genetic algorithm for content-based image retrieval. In: Proceedings of Asia Fuzzy Systems Symposium, pp. 479–484 (1998)

    Google Scholar 

  14. Kim, H.-S., Cho, S.-B.: Application of interactive genetic algorithm to fashion design. Engineering Application of Artificial Intelligence 13, 635–644 (2000)

    Article  Google Scholar 

  15. Li, J.Y.: A Web-based Intelligent Fashion Design System. Jounal of Donghua University 23(1), 36–41 (2006)

    Google Scholar 

  16. Wang, Y., Chen, Y., Chen, Z.-g.: The sensory research on the style of women’s overcoats. International Journal of Clothing Science and Technology 20(3), 174–183 (2008)

    Article  Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Li, J., Busemeyer, J.R. (2009). Combine the Objective Features with the Subjective Feelings in Personal Multi-alternative Decision Making Modeling. In: Zhong, N., Li, K., Lu, S., Chen, L. (eds) Brain Informatics. BI 2009. Lecture Notes in Computer Science(), vol 5819. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04954-5_29

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  • DOI: https://doi.org/10.1007/978-3-642-04954-5_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04953-8

  • Online ISBN: 978-3-642-04954-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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