What Is Computational Intelligence and Where Is It Going?

  • Włodzisław Duch
Part of the Studies in Computational Intelligence book series (SCI, volume 63)

Summary

What is Computational Intelligence (CI) and what are its relations with Artificial Intelligence (AI)? A brief survey of the scope of CI journals and books with “computational intelligence” in their title shows that at present it is an umbrella for three core technologies (neural, fuzzy and evolutionary), their applications, and selected fashionable pattern recognition methods. At present CI has no comprehensive foundations and is more a bag of tricks than a solid branch of science. The change of focus from methods to challenging problems is advocated, with CI defined as a part of computer and engineering sciences devoted to solution of non-algoritmizable problems. In this view AI is a part of CI focused on problems related to higher cognitive functions, while the rest of the CI community works on problems related to perception and control, or lower cognitive functions. Grand challenges on both sides of this spectrum are addressed.

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References

  1. [1]
    H.A. Simon, Artificial Intelligence: Where Has it Been, and Where is it Going? IEEE Transactions on Knowledge and Data Engineering 3(2): 128-136, 1991.CrossRefGoogle Scholar
  2. [2]
    A.K. Mackworth, The Coevolution of AI and AAAI, AI Magazine 26(4): 51-52, 2005.Google Scholar
  3. [3]
    J.C. Bezdek, What is computational intelligence? In: Computational Intelligence Imitating Life, pp. 1-12, IEEE Press, New York, 1994.Google Scholar
  4. [4]
    D. Poole, A. Mackworth and R. Goebel. Computational Intelligence - A Logical Approach. Oxford University Press, New York, 1998.MATHGoogle Scholar
  5. [5]
    Z. Chen, Computational Intelligence for Decision Support. CRC Press, Boca Raton, 2000. Google Scholar
  6. [6]
    A.P. Engelbrecht, Computational Intelligence: An Introduction. Wiley, 2003.Google Scholar
  7. [7]
    A. Konar, Computational Intelligence: Principles, Techniques and Applications. Springer 2005.Google Scholar
  8. [8]
    A. Kusiak, Computational Intelligence in Design and Manufacturing. Wiley-Interscience, 2000.Google Scholar
  9. [9]
    S. Dick and A. Kandel, Computational intelligence in software quality assurance. Series in Machine Perception and Artificial Intelligence, Vol. 63, World Scientific 2005.Google Scholar
  10. [10]
    R.E. King, Computational intelligence in control engineering, Marcel Dekker Inc., NY, 1999.Google Scholar
  11. [11]
    S.H. Chen, P. Wang, and P.P. Wang Computational Intelligence in Economics and Finance. Advanced Information Processing Series, Springer 2006.Google Scholar
  12. [12]
    A. Newell and H.A. Simon, Computer science as empirical enquiry: Symbols and search. Communications of the ACM 19(3), 113-126, 1976. CrossRefMathSciNetGoogle Scholar
  13. [13]
    A. Newell, Unified Theories of Cognition. Cambridge, MA: Harvard University Press 1990. Google Scholar
  14. [14]
    D. Lind, B. Marcus, Symbolic Dynamics and Coding, Cambridge University Press, 1995.Google Scholar
  15. [15]
    H. Jacobsson, Rule extraction from recurrent neural networks: A taxonomy and review. Neural Computation, 17(6), 1223-1263, 2005. MATHCrossRefMathSciNetGoogle Scholar
  16. [16]
    G. Lakoff, M. Johnson. Metaphors We Live By. University of Chicago Press, 2nd ed, 2003.Google Scholar
  17. [17]
    G. Lakoff, R. Núnez, Where Mathematics Comes From: How the Embodied Mind Brings Mathematics into Being. Basic Books 2000.Google Scholar
  18. [18]
    A. Clark, R. Lutz (eds), Connectionism in Context. Springer-Verlag, Berlin, 1992. Google Scholar
  19. [19]
    W. Duch and J. Mandziuk, Quo Vadis Computational Intelligence? In: Machine Intelligence: Quo Vadis? Advances in Fuzzy Systems - Applications and Theory (eds. P. Sincak, J. Vascak, K. Hirota), World Scientific, pp. 3-28, 2004.Google Scholar
  20. [20]
    D.E. Goldberg and G. Harik, A Case Study in Abnormal CI: The Design of Manufacturing and Other Anthropocentric Systems. International J. Computational Intelligence and Organizations, 1, 78-93, 1996. Google Scholar
  21. [21]
    D. Lenat and R.V. Guha, Building Large Knowledge-Based Systems:  Representation and Inference in the Cyc Project. Addison-Wesley 1990.Google Scholar
  22. [22]
    J. Szymanski, T. Sarnatowicz and W. Duch, Towards Avatars with Artificial Minds: Role of Semantic Memory. Journal of Ubiquitous Computing and Intelligence (in print)Google Scholar
  23. [23]
    E.A. Feigenbaum, Some Challenges and Grand Challenges for Computational Intelligence. Journal of the ACM 50(1), 32-40, 2003. CrossRefMathSciNetGoogle Scholar
  24. [24]
    R. Kurzweil. The age of spiritual machines: When computers exceed human intelligence. Penguin, New York, NY, 1999. Google Scholar
  25. [25]
    J. McCarthy, The Future of AIA Manifesto. AI Magazine 26, 39-40,2005.Google Scholar
  26. [26]
    L. Perlovsky. Knowledge Instinct. Basic Books, 2006.Google Scholar
  27. [27]
    W. Duch, Towards comprehensive foundations of computational intelligence. In: Duch W, Mandziuk J, Eds, Challenges for Computational Intelligence. Springer, pp. 261-316, 2007.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Włodzisław Duch
    • 1
  1. 1.Department of InformaticsNicolaus Copernicus UniversityTorunPoland

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