Temporal Planning with Intermediate Conditions and Effects
This addresses a specific bottleneck in automated temporal planning for systems requiring parallel actions and temporal constraints, representing an incremental improvement over existing methods.
The paper tackles the limitation of temporal planning systems that cannot specify conditions and effects at arbitrary points within action durations by introducing a heuristic-search technique that allows such specifications. The approach experimentally outperforms standard PDDL 2.1 encodings and is competitive with other methods handling intermediate conditions or effects.
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.