2021
DOI: 10.48550/arxiv.2111.12236
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Optimizing the Human Learnability of Abstract Network Representations

William Qian,
Christopher W. Lynn,
Andrei A. Klishin
et al.

Abstract: Precisely how humans process relational patterns of information in knowledge, language, music, and society is not well understood. Prior work in the field of statistical learning has demonstrated that humans process such information by building internal models of the underlying network structure. However, these mental maps are often inaccurate due to limitations in human information processing. The existence of such limitations raises clear questions: Given a target network that one wishes for a human to learn… Show more

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