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This paper solves the problem of computing the maximum (and minimum) probability to reach a set of goal states within a given time bound in continuous-time Markov decision processes (CTMDPs). For the subclass of locally uniform CTMDPs, we define the class of late total time positional schedulers (TTPDl) and prove that they suffice to resolve all nondeterministic choices in an optimal way. Our main...