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Complexity and cognitive computing

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Methodology and Tools in Knowledge-Based Systems (IEA/AIE 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1415))

Abstract

This paper proposes a hybrid expert system to minimize some of the complexity problems present in the artificial intelligence field such as the so-called bottleneck of expert systems, e.g., the knowledge elicitation process; the model choice for the knowledge representation to code human reasoning; the number of neurons in the hidden layer and the topology used in the connectionist approach, ; the difficulty to obtain the explanation on how the network arrived to a conclusion. To overcome these difficulties the cognitive computing was integrated to the developed system.

Currently at the Institut d'Informatique, FUNDP, Namur, Belgium: the work sponsored by CAPES, Brazil.

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References

  1. Johnson, R.C.: What is cognitive computing? Dr. Dobb's Journal (1993).

    Google Scholar 

  2. Holland, J.H.: Adaptation in Natural and Artificial Systems. MIT Press, Cambridge, MA (1975).

    Google Scholar 

  3. Hogan, J.M., Diederich, J: Random neural networks of biologically plausible connectivity. Complexity International, Vol. 2 (1996).

    Google Scholar 

  4. Rumelhart, D.E, Hinton, G.E., Willians, R.J.: Learning internal representations by error propagation. In: Rumelhart, D.E., McClelland, J.L., the PDP group.(eds.): Parallel Distributed Processing. Vol. 1. No. 2. MIT Press, Cambridge, Massachusetts (1987) 319–362.

    Google Scholar 

  5. Zadeh, L.A.: Fuzzy sets. Information and Control, Vol. 8 (1965) 338–354.

    Article  MATH  MathSciNet  Google Scholar 

  6. Gupta, M.M., Rao, D. H.: On the principles of fuzzy neural networks. Fuzzy Sets and Systems. vol. 61, no.1 (1994) 1–18.

    Article  MathSciNet  Google Scholar 

  7. Brasil, L. M., Azevedo, F.M., R. O., Garcia, Barreto, J.M.: Cooperation of symbolic and connectionist expert system techniques to overcome difficulties. in Proc. II Neural Networks Brazilian Congress. Curitiba, Brazil (1995) 177–182.

    Google Scholar 

  8. Brasil, L. M., Azevedo, F.M., R. O., Garcia, Barreto, J.M.: A Methodology for implementing hybrid expert systems. Proc. The IEEE Mediteranean Electrotechnical Conference, MELECON'96. Bary, Italy (1996) 661–664.

    Google Scholar 

  9. Brasil, L. M., Azevedo, F.M., Barreto, J.M.: Uma arquitetura híbrida para sistemas especialistas. Proc. III Neural Networks Brazilian Congress. Florianópolis, Brazil (1997) 167–172.

    Google Scholar 

  10. Brasil, L. M., Azevedo, F.M., Barreto, J.M.: Uma Arquitetura para Sistema Neuro-Fuzzy-Ga. Proc. of The III Congreso Chileno de Ingeniería Eléctrica, Universidad de La Frontera. Temuco, Chile (1997) 712–717.

    Google Scholar 

  11. Brasil, L. M., Azevedo, F.M., Barreto, J.M.: A hybrid expert architecture for medical diagnosis. Proc. 3th International Conference on Artificial Neural Networks and Genetic Algorithms, ICANNGA'97. Norwich, England (1997) 176–180.

    Google Scholar 

  12. Brasil, L. M., Azevedo, F.M., Barreto, J.M.: Learning algorithm for connectionist systems. Proc. XII Congreso Chileno de Ingeniería Eléctrica, Universidad de La Frontera. Temuco, Chile (1997) 697–702.

    Google Scholar 

  13. Brasil, L. M., Azevedo, F.M., Barreto, J.M., Noirhomme-Fraiture, M.: Training algorithm for neuro-fuzzy-ga systems. Proc. 16th IASTED International Conference on Applied Informatics, AI'98. Garmisch-Partenkirchen, Germany, February (1998) 697–702 (In Press).

    Google Scholar 

  14. Fogel, D.B.: Evolutionary Computation: Toward a New Philosophy of Machine Intelligence. IEEE Press, New York, USA (1995).

    Google Scholar 

  15. Azevedo, F.M. de: Contribution to the Study of Neural Networks in Dynamical Expert Systems. Ph.D. Thesis, Institut d'Informatique, FUNDP, Belgium (1993).

    Google Scholar 

  16. Mitra, S., Pal, S.K.: Logical operation based fuzzy MLP for classification and rule generation. Neural Networks. Vol. 7, No. 2 (1994) 25–29.

    Article  Google Scholar 

  17. Zhang, X., Hang, C., Tan, S., Wang, P.Z.: The min-max function differentiation and training of fuzzy neural networks. IEEE Transactions on neural networks. No. 5 (1994) 1139–1150.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Electrical Engineering, Federal University of Santa Catarina, University Campus, 88040-900, Florianópolis, Brazil

    Lourdes Mattos Brasil & Fernando Mendes de Azevedo

  2. Dept. of Informatics and Statistics, Federal University of Santa Catarina, University Campus, 88040-900, Florianópolis, Brazil

    Jorge Muniz Barreto

  3. Institut d'Informatique, FUNDP, Rue Grandgagnage, 21 B-5000, Namur, Belgium

    Lourdes Mattos Brasil & Monique Noirhomme-Fraiture

Authors
  1. Lourdes Mattos Brasil
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  2. Fernando Mendes de Azevedo
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  3. Jorge Muniz Barreto
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  4. Monique Noirhomme-Fraiture
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Editor information

José Mira Angel Pasqual del Pobil Moonis Ali

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© 1998 Springer-Verlag

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Brasil, L.M., Mendes de Azevedo, F., Barreto, J.M., Noirhomme-Fraiture, M. (1998). Complexity and cognitive computing. In: Mira, J., del Pobil, A.P., Ali, M. (eds) Methodology and Tools in Knowledge-Based Systems. IEA/AIE 1998. Lecture Notes in Computer Science, vol 1415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64582-9_771

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  • DOI: https://doi.org/10.1007/3-540-64582-9_771

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64582-5

  • Online ISBN: 978-3-540-69348-2

  • eBook Packages: Springer Book Archive

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