Accelerating partial order planners by improving plan and goal choices

We describe some simple domain-independent improvements to plan-reenement strategies for well-founded partial order planning that promise to bring this style of planning closer to practicality. One suggestion concerns the strategy for selecting plans for reenement among the current (incomplete) candidate plans. We propose an A* heuristic that counts only steps and open conditions, while ignoring \unsafe condi-tions" (threats). A second suggestion concerns the strategy for selecting open conditions (goals) to be established next in a selected incomplete plan. Here we propose a variant of a strategy suggested by Peot & Smith and studied by Joslin & Pollack; the variant gives top priority to unmatchable open conditions (enabling the elimination of the plan), second-highest priority to goals that can only be achieved uniquely, and otherwise uses LIFO prioritization. The preference for uniquely achievable goals is a \zero-commitment" strategy in the sense that the corresponding plan reenements are a matter of deductive certainty, involving no guesswork. In experiments based on modiications of UCPOP, we have obtained improvements by factors ranging from 5 to more than 1000 for a variety of problems that are nontrivial for the unmodiied version. Crucially, the hardest problems give the greatest improvements.