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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:11 Mar 2011 08:54

References in Article

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Goldstone, Robert (1994) Influences of categorization on perceptual discrimination. Journal of

Experimental Psychology: General, 1994 Jun, v123 (n2):178-200.

Harnad, S. (ed.) (1987) Categorical Perception: The Groundwork of Cognition. New York: Cambridge

University Press.

Harnad, S. (1990a) The Symbol Grounding Problem. Physica D 42: 335-346. [Reprinted in Hungarian

Translation as "A Szimbolum-Lehorgonyzas Problemaja." Magyar Pszichologiai Szemle

XLVIII-XLIX (32-33) 5-6: 365-383.]

Harnad, S. (1990b) Symbols and Nets: Cooperation vs. Competition. Review of: S. Pinker and J.

Mehler (Eds.) (1988) Connections and Symbols Connection Science 2: 257-260.

Harnad, S. (1992) Connecting Object to Symbol in Modeling Cognition. In: A. Clarke and R. Lutz

(Eds) Connectionism in Context Springer Verlag.

Harnad, S. (1993) Grounding Symbols in the Analog World with Neural Nets. Think 2(1) 12 - 78

(Special issue on "Connectionism versus Symbolism," D.M.W. Powers & P.A. Flach, eds.). [Also

reprinted in French translation as: "L'Ancrage des Symboles dans le Monde Analogique a l'aide de

Reseaux Neuronaux: un Modele Hybride." In: Rialle V. et Payette D. (Eds) La Modelisation.

LEKTON, Vol IV, No 2.]

Harnad, S. (1993) Symbol Grounding is an Empirical Problem: Neural Nets are Just a Candidate

Component. Proceedings of the Fifteenth Annual Meeting of the Cognitive Science Society. NJ:

Erlbaum

Harnad, S. (1994) Computation Is Just Interpretable Symbol Manipulation: Cognition Isn't. Special

Issue on "What Is Computation" Minds and Machines 4:379-390

Harnad, S. (1995) Grounding Symbolic Capacity in Robotic Capacity. In: Steels, L. and R. Brooks

(eds.) The "artificial life" route to "artificial intelligence." Building Situated Embodied Agents. New

Haven: Lawrence Erlbaum

Harnad, S., Hanson, S.J. & Lubin, J. (1991) Categorical Perception and the Evolution of Supervised

Learning in Neural Nets. In: Working Papers of the AAAI Spring Symposium on Machine Learning of

Natural Language and Ontology (DW Powers & L Reeker, Eds.) pp. 65-74. Presented at Symposium

on Symbol Grounding: Problems and Practice, Stanford University, March 1991; also reprinted as

Document D91-09, Deutsches Forschungszentrum fur Kuenstliche Intelligenz GmbH Kaiserslautern

FRG.

Harnad, S. Hanson, S.J. & Lubin, J. (1995) Learned Categorical Perception in Neural Nets:

Implications for Symbol Grounding. In: V. Honavar & L. Uhr (eds) Symbol Processors and

Connectionist Network Models in Artificial Intelligence and Cognitive Modelling: Steps Toward

Principled Integration. pp. 191-206. Acadamic Press.

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