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A Time-Dependent Distributed Processing Model of Stragtegy-Driven Inference Behavior
Abstract
Experimental evidence suggests that some readers make inference decisions early on in text understanding and mold the inferences from later text to fit with the eairlier inferences, while other readers postpone inference decisions until later in the text and then base their final interpretation of the text on those postponed inferences. This behavior has been called strategy-driven inference behavior because it wa^s originally ascribed to different strategies used by readers to guide the coiirse of their inference decisions. This paper presents a new theory of how this behavior comes about,attributing the observed differences in behavior not to different strategies but to very small differences in the underlying cognitive architecture. This theory is illustrated by a simple model of inference processing during text understanding. The inference processing model employs a hybrid connectionist network whose behavior is extremely sensitive to the order of activation of nodes in the network, which in turn corresponds to the order of presentation of events in the story.
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