  Automated temporal planning is the technology of choice when controlling
systems that can execute more actions in parallel and when temporal
constraints, such as deadlines, are needed in the model. One limitation of
several action-based planning systems is that actions are modeled as intervals
having conditions and effects only at the extremes and as invariants, but no
conditions nor effects can be specified at arbitrary points or sub-intervals.
In this paper, we address this limitation by providing an effective
heuristic-search technique for temporal planning, allowing the definition of
actions with conditions and effects at any arbitrary time within the action
duration. We experimentally demonstrate that our approach is far better than
standard encodings in PDDL 2.1 and is competitive with other approaches that
can (directly or indirectly) represent intermediate action conditions or
effects.
