After a summary of AI development, from its neurocybernetic origins to present paradigms, we establish the distinction between the description-based “top-down” approach and the mechanism-based “bottom-up” approach. Then we analyze the different types of neural circuits that repeatedly appear in the sensory, motor and association regions of the nervous system. Finally, we propose an abstraction process that allows us to interpret the functions of these circuits at knowledge level.


Conditioned Stimulus Unconditioned Stimulus Lateral Inhibition Neural Mechanism Knowledge Level 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. McCulloch, W.S.: Embodiments of Mind. The MIT Press, Cambridge (1965)Google Scholar
  2. Shapiro, S.C. (ed.): Encyclopedia of artificial intelligence, 2nd edn., vol. I & II. John Wiley & Sons, New York (1990)Google Scholar
  3. Brooks, R.A.: Intelligence without reason. A.i. memo, vol. 1293. MIT Press, Cambridge (1991)Google Scholar
  4. Clancey, W.J.: Situated cognition. On human knowledge and computer representation. Univ. Press, Cambridge (1997)Google Scholar
  5. Wiener, N.: Cybernetics. The Technology Press. J. Wiley & Sons, New York (1948)Google Scholar
  6. Beer, R.D.: Intelligence as adaptive behavior. Academic Press, London (1990)MATHGoogle Scholar
  7. Minsky, M.: The society of mind. Simon and Schuster, New York (1985)Google Scholar
  8. Russell, S., Norvig, P.: Artificial Intelligence. A Modern Approach. Prentice Hall, Upper Saddle River (1995)MATHGoogle Scholar
  9. Mira, J.: On the use of the computational paradigm in neurophysiology and cognitive science. In: Mira, J., Álvarez, J.R. (eds.) IWINAC 2005. LNCS, vol. 3561, pp. 1–15. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  10. Rosenblueth, A., Wiener, N., Bigelow, J.: Behavior, purpose and teleology. Philosophy of Science 10 (1943)Google Scholar
  11. Shannon, C.E., McCarthy, J. (eds.): Automata Studies. Princeton University Press, Princeton (1956)MATHGoogle Scholar
  12. Anderson, J.A., Rosenfeld, E. (eds.): Neurocomputing: Foundations of Research. The MIT Press, Cambridge (1989)Google Scholar
  13. Newell, A.: The knowledge level. AI Magazine 120 (1981)Google Scholar
  14. Marr, D.: Vision. Freeman, New York (1982)Google Scholar
  15. Maturana, H.R.: Ontology of observing. The biological foundations of self consciousness and the physical domain existence (2002), http://www.inteco.cl/biology/ontology/
  16. Varela, F.J.: Principles of Biological Autonomy. The North Holland Series in General Systems Research, New York (1979)Google Scholar
  17. Mira, J., Delgado, A.E.: Some comments on the antropocentric viewpoint in the neurocybernetic methodology. In: Proc. of the Seventh International Congress of Cybernetics and Systems, pp. 891–895 (1987)Google Scholar
  18. Murphy, R.R.: Introduction to AI robotics. MIT Press, Cambridge (2002)Google Scholar
  19. Schmitt, F.O., Worden, F.G.: The Neuroscience Fourth Study Program. The MIT Press, Cambridge (1979)Google Scholar
  20. Kandel, E.R., Schwartz, J.H., Jessell, T.M.: Principles of Neural Science. Prentice Hall, Englewood Cliffs (1991)Google Scholar
  21. Arbib, M. (ed.): The Handbook of Brain Theory and Neural Networks. The MIT Press, Cambridge (1995)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • José Mira Mira
    • 1
  1. 1.Dpto. de Inteligencia Artificial. ETS Ing. InformáticaUNEDMadridSpain

Personalised recommendations