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From Robotic Toil to Symbolic Theft: Grounding Transfer from Entry-Level to Higher-Level Categories

Cangelosi, Angelo and Greco, Alberto and Harnad, Stevan (2000) From Robotic Toil to Symbolic Theft: Grounding Transfer from Entry-Level to Higher-Level Categories. [Journal (Paginated)]

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Abstract

Neural network models of categorical perception (compression of within-category similarity and dilation of between-category differences) are applied to the symbol-grounding problem (of how to connect symbols with meanings) by connecting analog sensorimotor projections to arbitrary symbolic representations via learned category-invariance detectors in a hybrid symbolic/nonsymbolic system. Our nets are trained to categorize and name 50x50 pixel images (e.g., circles, ellipses, squares and rectangles) projected onto the receptive field of a 7x7 retina. They first learn to do prototype matching and then entry-level naming for the four kinds of stimuli, grounding their names directly in the input patterns via hidden-unit representations ("sensorimotor toil"). We show that a higher-level categorization (e.g., "symmetric" vs. "asymmetric") can learned in two very different ways: either (1) directly from the input, just as with the entry-level categories (i.e., by toil), or (2) indirectly, from boolean combinations of the grounded category names in the form of propositions describing the higher-order category ("symbolic theft"). We analyze the architectures and input conditions that allow grounding (in the form of compression/separation in internal similarity space) to be "transferred" in this second way from directly grounded entry-level category names to higher-order category names. Such hybrid models have implications for the evolution and learning of language.

Item Type:Journal (Paginated)
Keywords:symbol grounding, categorical perception, neural networks, robotics, language, perceptual learning recognition
Subjects:Psychology > Cognitive Psychology
Computer Science > Neural Nets
ID Code:1647
Deposited By: Harnad, Stevan
Deposited On:26 Jun 2001
Last Modified:11 Mar 2011 08:54

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