LOAIJun 22, 2021

Knowledge from Probability

arXiv:2106.11501v116 citations
Originality Incremental advance
AI Analysis

This work addresses foundational issues in epistemology and probability theory, offering a novel theoretical analysis.

The paper tackles the problem of analyzing inductive knowledge and belief through a probabilistic framework, predicting that only highly probable propositions are believed and that many principles of belief-revision fail.

We give a probabilistic analysis of inductive knowledge and belief and explore its predictions concerning knowledge about the future, about laws of nature, and about the values of inexactly measured quantities. The analysis combines a theory of knowledge and belief formulated in terms of relations of comparative normality with a probabilistic reduction of those relations. It predicts that only highly probable propositions are believed, and that many widely held principles of belief-revision fail.

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