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Learning Symbolic Names for Perceived Colors

By Johan M. Lammens and Stuart C. Shapiro


Introduction We are working on a computational model of color perception and color naming, which can be seen as an instance of symbol grounding [ 4 ] in the domain of color, or as an attempt to provide an artificial intelligent agent with embodied concepts of color. This effort is part of a larger one in the field of intelligent autonomous agents [ 8, 5 ] , and will provide a perceptual grounding for some of the symbolic representations in the SNePS Knowledge Representation formalism [ 13 ] , especially those referred to as "sensory nodes" [ 12 ] . The implemented model will allow an agent to name colors in its environment, point out examples of named colors in its environment, and learn new names for colors. Our research draws on work in the neurophysiology of color perception, particularly [ 3 ] , in semantic universals for natural languages, particularly [ 1 ] , and other work in AI and Cognitive Science. We discuss two area

Year: 2007
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