Article

Inferring the causes of noise from binary outcomes: A normative theory of learning under uncertainty

2026-03-03

Abstract excerpt

Inferring the true cause of noise—distinguishing between volatility (environmental change) and stochasticity (outcome randomness)—is essential for learning in noisy environments. While most studies rely on binary outcomes, previous models are designed for continuous outcome and use ad hoc approximations to handle binary data, introducing theoretical inconsistencies and interpretational issues. Here, we develop a n...

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Literature Corpus work: 224e8d99-7ab6-5b9a-8721-ec49971b71f0
DOI: 10.64898/2026.03.01.708925

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