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arXiv · 2412.06839

A Neural Model of Rule Discovery with Relatively Short-Term Sequence Memory

Naoya Arakawa
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Abstract

This report proposes a neural cognitive model for discovering regularities in event sequences. In a fluid intelligence task, the subject is required to discover regularities from relatively short-term memory of the first-seen task. Some fluid intelligence tasks require discovering regularities in event sequences. Thus, a neural network model was constructed to explain fluid intelligence or regularity discovery in event sequences with relatively short-term memory. The model was implemented and tested with delayed match-to-sample tasks.

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Naoya Arakawa. 2024-12-07. A Neural Model of Rule Discovery with Relatively Short-Term Sequence Memory. https://arxiv.org/abs/2412.06839

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