Preference revision and Bayesian updating

Abstract Classical Bayesian arguments show how coherence between preference and credence grounds the norm of Probabilism. But these arguments are almost entirely static: they explain only how preference and credence must fit together at a given time. Once preferences change, the question arises: how should credences be revised in response? I develop an axiomatic minimal-change preference revision theory, in which some preference commitments are treated as more trusted and serve as reference anchors in revision. Focusing on standard event-occurrence inputs, I compare the induced revision dynamics with those implied by Bayesian conditioning, as captured at the level of preferences. The main convergence result shows that treating prior conditional preferences (together with preferences over constant acts) as reference anchors yields a unique admissible posterior preference relation that coincides with the Bayes-induced posterior preference relation. The framework also isolates a principled mechanism for divergence: alternative anchoring stances—especially those privileging selected unconditional commitments over conditional ones—can force revisions to conditional attitudes and thereby generate systematic departures from the Bayes-induced posterior preference relation.