Cybernics pp 197-233 | Cite as

Subjectivity-Kansei Computing

  • Takehisa Onisawa


The chapter first discusses subjective Kansei information, with features such as subjectivity, ambiguity, vagueness and situation dependence, with respect to the interaction between a human and a computer agent. Next, soft computing techniques including fuzzy theory, neural network models, and evolutionary computation are introduced to deal with subjective Kansei information. Finally, this chapter presents some study examples of Subjectivity-Kansei computing using soft computing techniques.


Kansei information Cooperative agent Human–agent interaction Soft computing 


  1. 1.
    Japan Interdisciplinary Council (ed) (1993) Kansei and information processing–new possibility to computer science. Kyoritsu, TokyoGoogle Scholar
  2. 2.
    Iguchi S et al (1994) Kansei information processing. Ohmusha, TokyoGoogle Scholar
  3. 3.
    Tsuji S (1997) Science of Kansei – an approach to Kansei information processing. Saiensu-sha Co., Ltd., TokyoGoogle Scholar
  4. 4.
    Nagamachi M (1997) Kansei engineering and comfort – preface. Int J Ind Eng 19(1):79–80Google Scholar
  5. 5.
    Japan Society for Fuzzy Theory and Systems (ed) (1998) Panel discussion: Kansei engineering. J Jpn Soc Fuzzy Theory Syst 10(3):426–444Google Scholar
  6. 6.
  7. 7.
    Onisawa T (2000) Soft computing techniques in Kansei (emotional) information processing. In: Liu Z-Q, Miyamoto S (eds) Soft computing and human-centered machines. Springer, Tokyo, pp 215–248CrossRefGoogle Scholar
  8. 8.
    Onisawa T (2005) Soft computing in human centered systems thinking. In: Torra V, Narukawa Y, Miyamoto S (eds) Modeling decisions for artificial intelligence. Springer, Heidelberg, pp 36–46CrossRefGoogle Scholar
  9. 9.
    Onisawa T, Unehara M (2005) Application of interactive genetic algorithms to human-centered systems. J Soc Instrum Control Eng 44(1):50–57Google Scholar
  10. 10.
    Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353CrossRefMATHMathSciNetGoogle Scholar
  11. 11.
    Zadeh LA (1993) Applications of fuzzy technology and soft computing. J Jpn Soc Fuzzy Theory Syst 5:261–268Google Scholar
  12. 12.
    Li X, Ruan D, van der Wal AJ (1998) Discussion on soft computing at FLINS’96. Int J Intell Syst 13:287–300CrossRefGoogle Scholar
  13. 13.
    Zimmermann HJ (1985) Fuzzy sets theory – and its applications. Kluwer-Nijhoff, BostonCrossRefGoogle Scholar
  14. 14.
    Honda N, Ohsato A (1989) Introduction to fuzzy engineering. Kaibundo, TokyoGoogle Scholar
  15. 15.
    Cox E (1998) The fuzzy systems handbook, 2nd edn. Academic Press, Cambridge, MAGoogle Scholar
  16. 16.
    Kosoko B (1992) Neural networks and fuzzy systems, a dynamical systems approach to machine intelligence. Prentice-Hall, Englewood CiffsGoogle Scholar
  17. 17.
    Amari S (ed) (1993) New development of neural net. Saiensu-sha Co., Ltd., TokyoGoogle Scholar
  18. 18.
    Konar A (2000) Artificial intelligence and soft computing, behavioral and cognitive modeling of the human brain. CRC Press, Boca RatonGoogle Scholar
  19. 19.
    Kitano H (ed) (1993) Genetic algorithm. Sangyo-Tosho, TokyoGoogle Scholar
  20. 20.
    Fogel DB (1995) Evolutionary computation – toward a new philosophy of machine intelligence. IEEE Press, New YorkGoogle Scholar
  21. 21.
    Kitano H (ed) (2000) Genetic algorithm (4). Sangyo-Tosho, TokyoGoogle Scholar
  22. 22.
    Takagi H (2001) Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation. Proc IEEE 89(9):1275–1296CrossRefGoogle Scholar
  23. 23.
    Kolodner JL (1993) Case-based reasoning. Morgan Kaufmann, San MateoGoogle Scholar
  24. 24.
    Nitta K (2005) Knowledge and inference. Saiensu-sha Co., Ltd., TokyoGoogle Scholar
  25. 25.
    Hayashi J, Murakami K, Koshimizu H (1997) A method for automatic generation of caricature profile in PICASO system. Trans Inst Electron Inf Commun Eng D-II J80-D-II(8):2102–2109Google Scholar
  26. 26.
    Sato M, Saigo Y, Hashima K, Kasuga M (2003) An automatic facial caricature method for 2D realistic portraits using characteristic points. In: Journal of the 6th Asian design international conference, vol 1, E-40, TsukubaGoogle Scholar
  27. 27.
    Onisawa T, Hirasawa Y (2004) Facial caricature drawing using subjective image of a face obtained by words. In: Proceedings of 2004 I.E. international conference on fuzzy systems, Budapest, p 1370Google Scholar
  28. 28.
    Benhidour H, Onisawa T (2008) Interactive face generation from verbal description using conceptual fuzzy sets. J Multimed 3(2):52–59Google Scholar
  29. 29.
    Benhidour H, Onisawa T (2010) Interactive learning of verbal descriptors meanings for face drawing system. J Adv Comput Intell Intell Inform 14(6):606–615Google Scholar
  30. 30.
    Unehara M, Onisawa T (2003) Music composition system with human evaluation as human centered system. Soft Comput 7(3):167–178, SpringerCrossRefMATHGoogle Scholar
  31. 31.
    Unehara M, Onisawa T (2005) Music composition by interaction between human and computer. New Generat Comput 23(2):181–191, Ohmsha/Springer, TokyoGoogle Scholar
  32. 32.
    Ishizuka K, Onisawa T (2010) Operetta songs generation system based on impressions of story scenes. In: Proceedings of joint 5th international conference on soft computing and intelligent systems and 11th international symposium on advanced intelligent systems, Okayama, pp 831–836Google Scholar
  33. 33.
    Ogata Y, Onisawa T (2008) Interactive clothes design support system, LNCS 4985, revised selected papers (the 14th international conference on neural information processing, WMC-2, 2007), Springer, Kitakyushu, pp 657–665Google Scholar
  34. 34.
    Yamamoto S, Onisawa T (2009) Interactive support system for logotype design based on user’s feelings. In: Proceedings of the human interface symposium, Tokyo, pp 697–704Google Scholar
  35. 35.
    Ohsone K, Onisawa T (2008) Friendly partner system of poker game with facial expressions. In: Proceedings of 2008 I.E. symposium on computational intelligence and games, Perth, pp 95–102Google Scholar
  36. 36.
    Ohsone K, Onisawa T (2009) Cooperative partner agent of seven-card-stud poker. In: Proceedings of 2009 international fuzzy systems association world congress and 2009 European society for fuzzy logic and technology conference, Lisbon, pp 1595–1600Google Scholar
  37. 37.
    Osone K, Onisawa T (2011) Interactive learning agent of poker game. In: Proceedings of 12th international symposium on advanced intelligent systems, Suwon, pp 303–306Google Scholar
  38. 38.
    Gill KS (ed) (1996) Human machine symbiosis – the foundations of human-centred systems design. Springer, LondonGoogle Scholar
  39. 39.
    Picard RW (2000) Affective computing. The MIT Press, Cambridge, MAGoogle Scholar

Copyright information

© Springer Japan 2014

Authors and Affiliations

  1. 1.Faculty of Engineering, Information and SystemsUniversity of TsukubaTsukubaJapan

Personalised recommendations