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A connectionist-symbolic cognitive model

  • Knowledge Representation
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Methodologies for Intelligent Systems (ISMIS 1993)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 689))

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Abstract

This paper describes a formal model for the cognitive activity, which is an instantiation of a more general proposal for a research line in artificial intelligence. The main contribution of the paper is the specification of a wave propagation model that performs inference in predicate logic without quantifiers through an interference mechanism. The model is highly parallel, and is flexible enough to be extended, in a natural way, to simulate first-order logic, fuzzy logic, four-valued logic, and uncertain reasoning. The model is part of an architecture integrating neural networks and symbolic reasoning to simulate cognitive activities.

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References

  1. BELNAP, N.D., A Useful Four-Valued Logic. In “J.M. Dunn fand G. Epstein (Editors), Modern Uses of Multiple-Valued Logics”, D. Reidel Pub. Co., 1977.

    Google Scholar 

  2. BIRNBAUM, L., Rigor mortis: a response to Nilsson's “Logic and Artificial Intelligence”. Artificial Intelligence (Special Volume Foundations of Artificial Intelligence), Vol. 47, No. 1–3, pp. 57–77, January 1991.

    Google Scholar 

  3. BITTENCOURT, G., A Hybrid System Architecture and its Unified Semantics. In “Z.W. Ras (Editor), Proceedings of The Fourth International Symposium on Methodologies for Intelligent Systems”, Charlotte, North Caroline, USA, October 12–14, pp. 150–157, 1989.

    Google Scholar 

  4. BITTENCOURT, G. An Architecture for Hybrid Knowledge Representation. Ph.D. Thesis, Universität Karlsruhe, Deutschland, 31 Januar 1990.

    Google Scholar 

  5. BITTENCOURT, G. Space Embodiment and Natural Selection. Internal Report, INPE, 1993.

    Google Scholar 

  6. BROOKS, P.A., Intelligence without Representation. Artificial Intelligence (Special Volume Foundations of Artificial Intelligence), Vol. 47, No. 1–3, pp. 139–159, January 1991.

    Google Scholar 

  7. CHANGEUX, J.-P, L'Homme Neuronal. Collection Pluriel, Librairie ArthΩme Fayard, 1983.

    Google Scholar 

  8. HAMPDEN-TURNER, C., Maps of the Mind: Charts and Concepts of the Mind and its Labyrinths. Collter, New York, 1981.

    Google Scholar 

  9. HEARN, A.C., REDUCE User's Manual: Version 3.3. RAND Publication CP78, The RAND Corporation, Santa Barbara, CA, April 1987.

    Google Scholar 

  10. KIRSH, D., Foundations of AI: the Big Issues. Artificial Intelligence (Special Volume Foundations of Artificial Intelligence), Vol. 47, No. 1–3, pp. 3–30, January 1991a.

    Google Scholar 

  11. KIRSH, D., Today the Earwig, Tomorrow Man? Artificial Intelligence (Special Volume Foundations of Artificial Intelligence), Vol. 47, No. 1–3, pp. 161–184, January 1991b.

    Google Scholar 

  12. LUPASCO, S., L'énergie et la matière vivante. Antagonisme constructeur et logique de l'hétérogène. Juillard, Paris, 1974.

    Google Scholar 

  13. McCARTHY, J. and HAYES, P.J., Some Philosophical Problems from the Standpoint of Artificial Intelligence. In ”D. Mitchie and B. Meltzer (Editors), Machine Intelligence 4”, Edimburgh University Press, Edimbourgh, GB, pp. 463–502, 1969.

    Google Scholar 

  14. MINSKY, M.L. and PAPERT, S.A., Perceptrons: An Introduction to Computational Geometry. M.I.T. Press, 1969.

    Google Scholar 

  15. NEWELL, A. and SIMON, H.A., Computer Science as Empirical Inquiry: Systems and Search. Communications of the ACM, Vol. 19, No. 3, pp. 113–126, March 1976.

    Google Scholar 

  16. NILSSON, N.J., Logic and Artificial Intelligence. Artificial Intelligence (Special Volume Foundations of Artificial Intelligence), Vol. 47, No. 1–3, pp. 31–56, January 1991.

    Google Scholar 

  17. NORMAN, D.A., Approaches to the Study of Intelligence. Artificial Intelligence (Special Volume Foundations of Artificial Intelligence), Vol. 47, No. 1–3, pp. 327–346, January 1991.

    Google Scholar 

  18. PATEL-SCHNEIDER, P.F., A Decidable First-Order Logic for Knowledge Representation. Proceedings of IJCAI 9, pp. 455–458, 1985.

    Google Scholar 

  19. PRIBRAM, K., Language of the Brain: Experimental Paradoxes and Principles in Neuropsychology. Englewood Cliffs, N.J., Prentice Hall, 1971.

    Google Scholar 

  20. RUMELHART, D.E. and McCLELLAND, J. (Editors), Parallel Distributed Processing: Explorations in the Microstructure of Cognition 1: Foundations. M.I.T. Press, Cambridge, MA, 1986a.

    Google Scholar 

  21. RUMELHART, D.E. and McCLELLAND, J. (Editors), Parallel Distributed Processing: Explorations in the Microstructure of Cognition 2: Psychological and Biological Models. M.I.T. Press, Cambridge, MA, 1986b.

    Google Scholar 

  22. SMOLENSKY, P., Tensor Product Variable Binding and the Representation of Symbolic Structures in Connectionist Systems. Artificial Intelligence (Special Issue on Connectionist Symbol Processing), Vol. 46, No. 1–2, pp. 159–216, January 1991.

    Google Scholar 

  23. TORRANCE, S. (Editor), The Mind and the Machine: Philosophical Aspects of Artificial Intelligence. Ellis Horwood series in Artificial Intelligence, John Wiley & Sons, 1984.

    Google Scholar 

  24. WEST, D.M. and TRAVIS, L.E., From Society to Landscape: Alternative Metaphors for Artificial Inelligence. AI Magazine, pp. 69–83, Summer 1991.

    Google Scholar 

  25. ZADEH, L.A., Fuzzy Logic and Approximate Reasoning. Synthese, Vol. 30, pp. 407–428, 1975.

    Google Scholar 

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Jan Komorowski Zbigniew W. Raś

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© 1993 Springer-Verlag Berlin Heidelberg

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Bittencourt, G. (1993). A connectionist-symbolic cognitive model. In: Komorowski, J., Raś, Z.W. (eds) Methodologies for Intelligent Systems. ISMIS 1993. Lecture Notes in Computer Science, vol 689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56804-2_50

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  • DOI: https://doi.org/10.1007/3-540-56804-2_50

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  • Print ISBN: 978-3-540-56804-9

  • Online ISBN: 978-3-540-47750-1

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