Abstract
A menu-driven software system was developed to implement schemata organization in a constraint-satisfaction neural network. The current neural-net model present several advantages and modifications over previous related models. On the one hand, the schemata behavior shown by the present model is based on conceptual definitions and ratings obtained empirically from human subjects rather than on the idiosyncratic knowledge database of a single programmer. On. the other hand, this property is most valuable to experimental research in which the current knowledge status of the subjects is critical for the experiments (e.g., word-recognition experiments).
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