  Model checking probabilistic CTL properties of Markov decision processes with
convex uncertainties has been recently investigated by Puggelli et al. Such
model checking algorithms typically suffer from the state space explosion. In
this paper, we address probabilistic bisimulation to reduce the size of such an
MDP while preserving the probabilistic CTL properties it satisfies. In
particular, we discuss the key ingredients to build up the operations of
parallel composition for composing interval MDP components at run-time. More
precisely, we investigate how the parallel composition operator for interval
MDPs can be defined so as to arrive at a congruence closure. As a result, we
show that probabilistic bisimulation for interval MDPs is congruence with
respect to two facets of parallelism, namely synchronous product and
interleaving.
