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Automated temporal planning is the technology of choice when controllingsystems that can execute more actions in parallel and when temporalconstraints, such as deadlines, are needed in the model. One limitation ofseveral action-based planning systems is that actions are modeled as intervalshaving conditions and effects only at the extremes and as invariants, but noconditions nor effects can be specified at arbitrary points or sub-intervals.In this paper, we address this limitation by providing an effectiveheuristic-search technique for temporal planning, allowing the definition ofactions with conditions and effects at any arbitrary time within the actionduration. We experimentally demonstrate that our approach is far better thanstandard encodings in PDDL 2.1 and is competitive with other approaches thatcan (directly or indirectly) represent intermediate action conditions oreffects.

Temporal Planning with Intermediate Conditions and Effects