 Many probability logics are interpreted over a single, but arbitrary probability space. Modal probability logic makes use of many probability spaces, each associated with a possible world or state. This can be viewed as a minor adjustment to the relational semantics of modal logic: rather than associate to every possible world a set of accessible worlds as is done in modal logic, modal probability logic associates to every possible world a probability distribution, a probability space, or a set of probability distributions. The language of modal probability logic allows for embedding of probabilities within probabilities, that is, it can for example reason about the probability that (possibly a different) probability is \(1/2\). This modal setting involving multiple probabilities has generally been given a (1) stochastic interpretation, concerning different probabilities over the next states a system might transition into (Larsen and Skou 1991), and (2) a subjective interpretation, concerning different probabilities that different agents may have about a situation or each other’s probabilities (Fagin and Halpern 1988). Both interpretations can use exactly the same formal framework.