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Grounding symbols in sensorimotor categories with neural networks

Harnad, Stevan (1995) Grounding symbols in sensorimotor categories with neural networks. [Conference Paper]

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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).

Item Type:Conference Paper
Keywords:cognition, computation, symbol grounding, neural networks
Subjects:Computer Science > Artificial Intelligence
Computer Science > Dynamical Systems
Computer Science > Neural Nets
Psychology > Perceptual Cognitive Psychology
ID Code:1593
Deposited By:Harnad, Stevan
Deposited On:19 Jun 2001
Last Modified:19 Dec 2009 19:17

References in Article

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