Grounding symbols in sensorimotor categories with neural networks
Institute of Electrical Engineers Colloquium on "Grounding Representations (1995)
| Abstract | It is unlikely that the systematic, compositional properties of formal symbol systems -- i.e., of computation -- play no role at all in cognition. However, it is equally unlikely that cognition is just computation, because of the symbol grounding problem (Harnad 1990): The symbols in a symbol system are systematically interpretable, by external interpreters, as meaning something, and that is a remarkable and powerful property of symbol systems. Cognition (i.e., thinking), has this property too: Our thoughts are systematically interpretable by external interpreters as meaning something. However, unlike symbols in symbol systems, thoughts mean what they mean autonomously: Their meaning does not consist of or depend on anyone making or being able to make any external interpretations of them at all. When I think "the cat is on the mat," the meaning of that thought is autonomous; it does not depend on YOUR being able to interpret it as meaning that (even though you could interpret it that way, and you would be right). | |||||||||
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Similar books and articlesStevan Harnad (1992). Connecting Object to Symbol in Modeling Cognition. In A. Clark & Ronald Lutz (eds.), Connectionism in Context. Springer-Verlag.
Vincent C. Müller (2009). Symbol Grounding in Computational Systems: A Paradox of Intentions. Minds and Machines 19 (4):529-541.
Stevan Harnad (2002). Symbol Grounding and the Origin of Language. In Matthias Scheutz (ed.), Computationalism: New Directions. MIT Press.
Stevan Harnad (1994). Computation is Just Interpretable Symbol Manipulation; Cognition Isn't. Minds and Machines 4 (4):379-90.
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