Advertisement

Granular Structure Model Based on Artificial Emotion

  • Jun Hu
  • Chun Guan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 99)

Abstract

Granular computing theory is an important tool for processing vague, incomplete, inaccurate information. Based on the granular computing theory, a new artificial emotion granular structure model is proposed in this paper. The model presents a new artificial emotion granular concept and defines some key factors. Finally, an experiment is given to calculate and verify the emotion granular structure model.

Keywords

Granular Emotion Model 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Nahl, D.: Affective computing. Information Processing & Management 34(4), 510–512 (1998)CrossRefGoogle Scholar
  2. 2.
    Jin, H., Gao, W.: The human facial combined expression recognition system. Chinese Journal of Computers 23(6), 202–208 (2000)Google Scholar
  3. 3.
    Song, Y., Jia, P.: A control architecture based on artificial emotion for anthropomorphic. Robot 26(6), 491–495 (2004)Google Scholar
  4. 4.
    Wang, Y., Yuan, B.: Pen-based gesture recognition in multi-modal human-computer interaction. Journal of Northern Jiaotong University (2), 10–13 (2001)Google Scholar
  5. 5.
    Picard, R.W.: Affective computing. MIT Press, London (1997)Google Scholar
  6. 6.
    Sloman, A., Croucher, M.: Why robots will have emotions. In: Proceedings IJCAI, Vancouver (1981)Google Scholar
  7. 7.
    Ward, R.D., Marsden, P.H.: Affective computing: prob1ems, reactions and intentions. Interacting with Computers 16(4), 707–713 (2004)CrossRefGoogle Scholar
  8. 8.
    Zadeh, L.A.: Fuzzy sets and information granulation. Advances in fuzzy set theory and applications. North-Holland Publishing, Amsterdam (1979)Google Scholar
  9. 9.
    Hobbs, J.R.: Granularity, Proc. of the Ninth International Joint Conference on Artificial Intelligence, Los Angeles (1985)Google Scholar
  10. 10.
    Frijda, N.: Recognition of Emotion. Advances in Experimental Social Psychology, 167–223 (1969)Google Scholar
  11. 11.
    Pawlak, Z.: Rough sets. International Journal of Computer and Information Sciences 11, 341–356 (1982)zbMATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Liu, Q.: Rough Sets and Rough Reasoning, 3rd edn. Science Press, Beijing (2005)Google Scholar
  13. 13.
    Picard, R.W.: Affective computing. MIT Press, London (1997)Google Scholar
  14. 14.
    Chen, B., Sun, M., Zhou, M.: Granular Rough Theory: A representation semantics oriented theory of roughness. Applied Soft Computing 9(2), 786–805 (2009)CrossRefGoogle Scholar
  15. 15.
    Han, J.C., Lin, T.Y.: Granular computing: Models and applications. International Journal of Intelligent Systems 25(2), 111–117 (2010)MathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jun Hu
    • 1
  • Chun Guan
    • 2
  1. 1.School of SoftwareNanchang UniversityNanchangChina
  2. 2.School of Information EngineeringNanchang UniversityNanchangChina

Personalised recommendations