Article

Asymmetric learning and adaptability to changes in relational structure during transitive inference

2024-07-05

Abstract excerpt

Humans and other animals can generalise from local to global relationships in a transitive manner. Recent research has shown that asymmetrically biased learning, where beliefs about only the winners (or losers) of local comparisons are updated, is well-suited for inferring relational structures from sparse feedback. However, less is known about how belief-updating biases intersect with humans’ capacity to adapt to...

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Literature Corpus work: 481f5200-1d90-5866-9f4d-c13f18dbf7d5
DOI: 10.1101/2024.07.03.601844

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