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Resolving the Symbol-Subsymbol Debates

  • Tiansi DongEmail author
Chapter
  • 260 Downloads
Part of the Studies in Computational Intelligence book series (SCI, volume 910)

Abstract

The symbol spatialization process creates a new geometric layer between the connectionist layer and the symbolic layer. Connectionist networks produce vectors; Geometric layers promote these vectors into \(\mathscr {N}\)-Balls in higher dimensions.

References

  1. Antony, L., & Levine, J. (1988). On the proper treatment of the connection between connectionism and symbolism. Behavioral and Brain Sciences, 1, 23–44.CrossRefGoogle Scholar
  2. Bechtel, W. (1988). Connection and interlevel relationism. Behavioral and Brain Sciences, 1, 24–25.CrossRefGoogle Scholar
  3. Belew, R. K. (1988). Two constructive themes. Behavioral and Brain Sciences, 1, 25–26.CrossRefGoogle Scholar
  4. Carey, S. (2009). The origin of concepts. Oxford University Press.Google Scholar
  5. Cleland, C. E. (1988). Is Smolensky’s treatment of connectionism on the level? Behavioral and Brain Sciences, 1, 27–28.CrossRefGoogle Scholar
  6. Dellarosa, D. (1988). The psychological appeal of connectionism. Behavioral and Brain Sciences, 1, 28–29.CrossRefGoogle Scholar
  7. Dietrich, E., & Fields, C. (1988). Some assumptions underlying Smolensky’s treatment of connectionism. Behavioral and Brain Sciences, 1, 29–31.CrossRefGoogle Scholar
  8. Dong, T. (2008). A comment on RCC: From RCC to RCC++. Journal of Philosophical Logic, 37(4), 319–352.MathSciNetCrossRefGoogle Scholar
  9. Dong, T. (2012). Recognizing variable environments—The theory of cognitive prism, Volume 388 of Studies in computational intelligence. Berlin, Heidelberg: Springer.Google Scholar
  10. Dyer, M. G. (1988). The promise and problems of connectionism. Behavioral and Brain Sciences, 1, 32–33.CrossRefGoogle Scholar
  11. Elkan, C. (1993). The paradoxical success of fuzzy logic. IEEE Expert, 698–703.Google Scholar
  12. Grosse, R. B., Salakhutdinov, R., Freeman, W. T., & Tenenbaum, J. B. (2012). Exploiting compositionality to explore a large space of model structures. In Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, UAI’12 (pp. 306–315). Arlington, Virginia, USA: AUAI Press.Google Scholar
  13. Hunter, L. E. (1988). Some memory, but no mind. Behavioral and Brain Sciences, 1, 37–38.CrossRefGoogle Scholar
  14. Kemp, C., & Tenenbaum, J. B. (2008). The discovery of structural form. Proceedings of the National Academy of Sciences, 105, 10687–10692.CrossRefGoogle Scholar
  15. Lakoff, G. (1988). Smolensky, semantics, and the sensorimotor system. Behavioral and Brain Sciences, 1, 39–40.CrossRefGoogle Scholar
  16. Levinson, S. (1996). Frames of reference and Molyneux’s question: Cross-linguistic evidence. In P. Bloom, M. A. Peterson, L. Nadel, & M. F. Garrett (Eds.), Space and language (pp. 109–169). Cambridge: MIT Press.Google Scholar
  17. Li, X., Vilnis, L., Zhang, D., Boratko, M., & McCallum, A. (2019). Smoothing the geometry of box embeddings. In International Conference on Learning Representations (ICLR).Google Scholar
  18. Lu, S., Mao, J., Tenenbaum, J., & Wu, J. (2019). Neurally-guided structure inference. In K. Chaudhuri & R. Salakhutdinov (Eds.), Proceedings of the 36th International Conference on Machine Learning, Volume 97 of Proceedings of Machine Learning Research (pp. 4144–4153). Long Beach, California, USA: PMLR.Google Scholar
  19. Luria, A. R. (1966). Higher cortical functions in man. USA: Springer.Google Scholar
  20. McCarthy, J. (1988). Epistemological challenges for connectionism. Behavioral and Brain Sciences, 1, 44.CrossRefGoogle Scholar
  21. Nelson, R. J. (1988). Connections among connections. Behavioral and Brain Sciences, 1, 45–46.CrossRefGoogle Scholar
  22. Piaget, J., & Inhelder, B. (1948). La représentation de l’espace chez l’enfant. Bibliothèque de Philosophie Contemporaine, Paris: PUF. English translation by F. J. Langdon and J. L. Lunzer in 1956.Google Scholar
  23. Pinker, S. (1984). Language learnability and language development. Harvard University Press.Google Scholar
  24. Pinker, S., & Prince, A. (1988). On language and connectionism: Analysis of a parallel distributed processing model of language acquisition. Cognition, 28, 73–193.CrossRefGoogle Scholar
  25. Prince, A., & Pinker, S. (1988). Subsymbols aren’t much good outside of a symbol-processing architecture. Behavioral and Brain Sciences, 1, 46–47.CrossRefGoogle Scholar
  26. Rueckl, J. G. (1988). Making the connections. Behavioral and Brain Sciences, 1, 50–51.CrossRefGoogle Scholar
  27. Sejnowski, T. J., & Rosenberg, C. R. (1988). Neurocomputing: Foundations of research. In NETtalk: A parallel network that learns to read aloud (pp. 661–672). Cambridge, MA, USA: MIT Press.Google Scholar
  28. Smith, B. (1994). Topological foundations of cognitive science. In C. Eschenbach, C. Habel, & B. Smith (Eds.), Topological foundations of cognitive science. Buffalo, NY: Workshop at the FISI-CS.Google Scholar
  29. Smith, B. (2001). Fiat objects. Topoi, 20(2), 131–148.CrossRefGoogle Scholar
  30. Smolensky, P. (1988a). Putting together connectionism—Again. Behavioral and Brain Sciences, 1, 59–70.Google Scholar
  31. Smolensky, P. (1988b). On the proper treatment of connectionism. Behavioral and Brain Sciences, 1, 1–23.Google Scholar
  32. Sun, R. (2016). Implicit and explicit processes: Their relation, interaction, and competition. In L. Macchi, M. Bagassi, & R. Viale (Eds.), Cognitive unconscious and human rationality (pp. 27–257). Cambridge, MA: MIT Press.Google Scholar
  33. Sun, R., & Helie, S. (2010). Incubation, insight, and creative problem solving: A unified theory and a connectionist model. Psychological Review, 117(3), 994–1024.CrossRefGoogle Scholar
  34. Sun, R., Slusarz, P., & Terry, C. (2005). The interaction of the explicit and the implicit in skill learning: A dual-process approach. Psychological Review, 112(1), 159–192.CrossRefGoogle Scholar
  35. Woodfield, A., & Morton, A. (1988). The reality of the symbolic and subsymbolic systems. Behavioral and Brain Sciences, 1, 58.CrossRefGoogle Scholar
  36. Zadeh, L. A. (1965). Fuzzy sets. Informations and Control, 8, 338–353.CrossRefGoogle Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.ML2R Competence Center for Machine Learning Rhine-Ruhr, MLAI Lab, AI Foundations Group, Bonn-Aachen International Center for Information Technology (b-it)University of BonnBonnGermany

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