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.

翻译：我们提出动态概率运动学（DPK），这是一种让主体在部分信息存在下机械更新主观信念的方法。随后，我们将DPK推广至动态不精确概率运动学（DIPK），该方法允许主体通过一组概率表达其初始信念，以进一步考虑模糊性。我们给出了与更新后概率集相关的下概率的界限，并研究了后者的行为，特别是收缩、扩张与确定损失。文中提供了示例来说明这些方法的运作方式。