Real world temporal planning often involves dealing with uncertainty about the duration of actions. In this paper, we describe a sound-and-complete compilation technique for strong planning that reduces any planning instance with uncertainty in the duration of actions to a plain temporal planning problem without uncertainty. We evaluate our technique by comparing it with a recently-presented technique for PDDL domains with temporal uncertainty. The experimental results demonstrate the practical applicability of our approach and show a complementary behavior with respect to the previous techniques. We also demonstrate the high expressiveness of the translation by applying it to a significant fragment of the ANML language.
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