  Prominent approaches to belief revision prescribe the adoption of a new
belief that is as close as possible to the prior belief, in a process that,
even in the standard case, can be described as attempting to minimize surprise.
Here we extend the existing model by proposing a measure of surprise, dubbed
relative surprise, in which surprise is computed with respect not just to the
prior belief, but also to the broader context provided by the new information,
using a measure derived from familiar distance notions between truth-value
assignments. We characterize the surprise minimization revision operator thus
defined using a set of intuitive rationality postulates in the AGM mould, along
the way obtaining representation results for other existing revision operators
in the literature, such as the Dalal operator and a recently introduced
distance-based min-max operator.
