creators_name: Harnad, Stevan creators_name: Hanson, Stephen J. creators_name: Lubin, Joseph editors_name: Honavar, V. editors_name: Uhr, L. type: bookchapter datestamp: 2001-06-19 lastmod: 2011-03-11 08:54:41 metadata_visibility: show title: Learned Categorical Perception in Neural Nets: Implications for Symbol Grounding ispublished: pub subjects: comp-sci-mach-dynam-sys subjects: comp-sci-neural-nets subjects: percep-cog-psy full_text_status: public keywords: Neural nets, symbol grounding, categorical perception abstract: After people learn to sort objects into categories they see them differently. Members of the same category look more alike and members of different categories look more different. This phenomenon of within-category compression and between-category separation in similarity space is called categorical perception (CP). It is exhibited by human subjects, animals and neural net models. In backpropagation nets trained first to auto-associate 12 stimuli varying along a one-dimensional continuum and then to sort them into 3 categories, CP arises as a natural side-effect because of four factors: (1) Maximal interstimulus separation in hidden-unit space during auto-association learning, (2) movement toward linear separability during categorization learning, (3) inverse-distance repulsive force exerted by the between-category boundary, and (4) the modulating effects of input iconicity, especially in interpolating CP to untrained regions of the continuum. Once similarity space has been "warped" in this way, the compressed and separated "chunks" have symbolic labels which could then be combined into symbol strings that constitute propositions about objects. The meanings of such symbolic representations would be "grounded" in the system's capacity to pick out from their sensory projections the object categories that the propositions were about. date: 1995 date_type: published publication: Symbol Processors and Connectionist Network Models in Artificial Intelligence and Cognitive Modelling: Steps Toward Principled Integration publisher: Academic Press pagerange: 191-206 refereed: FALSE referencetext: Andrews, J., Livingston, K., Harnad, S. & Fischer, U. (1992) Learned Categorical Perception in Human Subjects: Implications for Symbol Grounding. Berlin, B. & Kay, P. (1969) Basic color terms: Their universality and evolution. Berkeley: University of California Press Bornstein, M. H. (1987) Perceptual Categories in Vision and Audition. In: Harnad (1987) Boynton, R. M. (1979) Human color vision. New York: Holt, Rinehart, Winston Cottrell, Munro & Zipser (1987) Image compression by back propagation: an example of extensional programming. 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