Abstract

How do internal symbols become connected to the object they stand for?$\sp1$ A symbol system is a set of physical objects or states and the formal rules for manipulating them. The rules are syntactic, operating only on the shapes of the symbols, not their meanings. Yet the symbol combinations can be given a systematic interpretation or states of affairs ). These meanings, however, are not "grounded"; they derive from the mind of the interpreter of the symbols. How can the meanings of symbols be grounded without the mediation of an interpreter? This is the "symbol grounding problem." ;Symbol grounding is not possible in a pure symbol system, but in a hybrid system with nonsymbolic robotic capacities such as transduction, analog transformation and sensory invariance extraction, the meanings of elementary symbols can be grounded in the system's capacity to discriminate and categorize the analog objects and states of affairs that its internal symbols stand for, based on the invariants in the sensory projections of those objects and states of affairs. The grounded elementary symbols can then be rulefully combined to form higher-order symbol combinations that inherit the grounding as nonarbitrary constraints on their shapes. ;"Categorical Perception" occurs when there is a special interaction between discrimination and identification performance : Stimuli that are in the same category and have the same name resemble one another more than stimuli that are in different categories and have different names, even when the physical differences between them are equal. This "warping" of similarity space, the hallmark of CP, suggests a model for grounding higher-order categories in sensory categories: In a three-level representational system the top, symbolic level, can be grounded bottom-up in the lower two, the analog and categorical levels. ;This model was tested with neural net simulations using one-dimensional inputs: When a net is trained to discriminate and then categorize a set of stimuli, the categorization task is accomplished by "warping" the similarity space , the same natural side-effect found in human and animal CP. These compressed, identified regions of similarity space may be the ground level out of which higher-order categories are constructed. Nets are one possible mechanism for learning the sensorimotor invariants that connect arbitrary names to the nonarbitrary shapes of the objects they stand for, thereby mediating the constraints exerted by the analog world of objects on the formal world of symbols. ftn$\sp1$This thesis is based on four published papers