From Probability to Consilience: How Explanatory Values Implement Bayesian Reasoning

Published on October 24, 2020

Recent work in cognitive science has uncovered a diversity of explanatory values, or dimensions along which we judge explanations as better or worse. We propose a Bayesian account of these values that clarifies their function and shows how they fit together to guide explanation-making. The resulting taxonomy shows that core values from psychology, statistics, and the philosophy of science emerge from a common mathematical framework and provide insight into why people adopt the explanations they do.

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