ACT-R model predicts who draws atypicality inferences
Original title: Modeling individual and item differences in atypicality inferences with ACT-R
Parameters are estimated from Raven's Matrices scores, typicality ratings, and language-model accommodation likelihood.
The paper models why people differ in inferring that a mentioned, highly predictable event is atypical. A resource-rational ACT-R model selects interpretation strategies from individual exploration tendencies and item-level predispositions. Those parameters are estimated independently of the inference task.
- Experimental items vary in inference rates with event typicality.
- Inferences are not drawn uniformly across individuals.
- Results are tied to recent findings from reference games.
From the original article
1 min read at arxiv.orgHumans engage in pragmatic reasoning when encountering mentions of highly predictable events. Such mentions may appear redundant, leading comprehenders to infer that the event is atypical, and accommodate this inference with an explanation for why it is atypical. However, these inferences are not drawn uniformly across individuals, and experimental items vary in inference rates due to differences in event typicality.
By Guifu Liu · arxiv.org
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