  We introduce dynamic probability kinematics (DPK), a method for an agent to
mechanically update subjective beliefs in the presence of partial information.
We then generalize DPK to dynamic imprecise probability kinematics (DIPK),
which allows the agent to express their initial beliefs via a set of
probabilities in order to further take ambiguity into account. We provide
bounds for the lower probability associated with the updated probability sets,
and we study the behavior of the latter, in particular contraction, dilation,
and sure loss. Examples are provided to illustrate how the methods work.
