  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 how these values fit together to guide
explanation. The resulting taxonomy provides a set of predictors for which
explanations people prefer and shows how core values from psychology,
statistics, and the philosophy of science emerge from a common mathematical
framework. In addition to operationalizing the explanatory virtues associated
with, for example, scientific argument-making, this framework also enables us
to reinterpret the explanatory vices that drive conspiracy theories, delusions,
and extremist ideologies.
