Abstract
This paper deals with symbol formation, from a cognitive point of view, through a connectionist model.
To give an idea of our aim, let us consider the metaphor of learning to play tennis. Two knowledge forms are involved:
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- implicit knowledge, e.g. sensori-motor associations; this knowledge is subsymbolic
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- explicit knowledge, e.g. a teacher giving verbal advice, which makes use of symbols.
Learned knowledge consists of a combination of subsymbolic and symbolic items. More than a juxtaposition, this combination involves grounding symbols into a subsymbolic substratum. This leads us to connectionist modelling which is considered as the common framework for both kinds of knowledge.
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References
Barto, A. G. & Sutton, R. S. (1981). Landmark Learning: An Illustration of Associative Search. Biological Cybernetics 42: 1–8.
Grumbach, A. (1994) Cognition artificielle, Du réflexe ... à la réflexion. Addison Wesley: Paris.
Hendler, J. (1991). Developing Hybrid Symbolic/Connectionist Models. In Barnden, J. (ed.) Advances in Connectionist and Neural Computation Theory, Ch. 7, pp. 165–179.
Hofstadter, D. (1980). Gödel, Escher, Bach. Vintage Books, pp. 349.
Nenov, V. I. & Dyer, M. G. (1988). DETE System: Connectionists/Symbolic Model of Visual Verbal Association. Proceedings of the International Conference on Neural Networks, Vol. II, pp. 17–24.
Ogden, C. K. & Richards, I. A. (1923). The Meaning of Meaning. Routledge and Kegan Paul: London.
Piaget, J. (1978). La formation du symbole chez l'enfant. Delachaux et Niestlé: Neuchâtel-Paris.
Regier, T. (1992). The Acquisition of Lexical Semantics for Spatial Terms: A Connectionist Model of Perceptual Categorization. Computer Science Division, EECS Department, University of California Berkeley dissertation, TR-92-062.
Shastri, L. & Feldman, J. A. (1984). Semantic Networks and Neural Nets. University of Rochester, TR 131.
Shavlik, J. W. (1992). A Framework for Combining Symbolic and Neural Learning. Computer Science Dept., University of Wisconsin-Maddison, TR 1123.
Sorouchyari, E. (1989). Mobile Robot Navigation: A Neural Network Approach. Proceedings of Journées d'Electronique, Ecole Polytechnique Fédérale de Lausanne, pp. 159–175.
Ritter, H., Martinez, T. & Schulten, K. (1989). Topology Conserving Maps for Learning Visuo-Motor Coordination. Neural Networks 2: 159–168.
Towell, G. G. & Shavlik, J. W. (1994). Knowledge-Based Artificial Neural Network. Artificial Intelligence 70, Nos. 1–2, 119–165.
Werner, H. & Kaplan, B. (1963). Symbol Formation. Wiley: New York.
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This research was supported by French CNRS “Réseau Cogni-Centre” and “GDR 957”. This paper is published by courtesy of HERMES editor who published a previous French version in “Technique et Science Informatiques” Vol. 12, no. 3, 1993, pp. 347–369.
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Grumbach, A. Grounding symbols into perceptions. Artif Intell Rev 10, 131–146 (1996). https://doi.org/10.1007/BF00159219
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DOI: https://doi.org/10.1007/BF00159219