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Modeling Inter-Category Topicality within a Symbolic Search Framework

Abstract

This paper addresses category typicality in the context of a category naming task. In contrast to the predominant effort with gradient models, a symbolic search framework is taken. Within this framework, the SC A (Symbolic Concept Acquisition) model demonstrates varying response times as a function of an instance's intra-category typicality. Here its coverage is expanded to inter-category typicality. A functionally motivated extension for SC A is advanced that pursues search backtracking under ambiguous cases. I explain how the backtracking extension accounts for inter-category typicality effects, and support it with some empirical evidence. I discuss how the effect generalizes to a larger class of symbolic search models.

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