On Delete Relaxation in Partial-Order Causal-Link Planning

We prove a new complexity result for Partial-Order Causal-Link (POCL) planning which shows the hardness of refining a search node (i.e., a partial plan) to a valid solution given a delete effect-free domain model. While the corresponding decision problem is known to be polynomial in state-based search (where search nodes are states), it turns out to be intractable in the POCL setting. Since both of the currently best-informed heuristics for POCL planning are based on delete relaxation, we hope that our result sheds some new light on the problem of designing heuristics for POCL planning. Based on this result, we developed a new variant of one of these heuristics which incorporates more information of the current partial plan. We evaluate our heuristic on several domains of the early International Planning Competitions and compare it with other POCL heuristics from the literature.