Optimal planning for delete-free tasks with incremental LM-cut

Abstract

Optimal plans of delete-free planning tasks are interesting both in domains that have no delete effects and as the relaxation heuristic h + in general planning. Many heuristics for optimal and satisficing planning approximate the h + heuristic, which is well-informed and admissible but intractable to compute. In this work, branch-and-bound and IDA* search are used in a search space tailored to delete-free planning together with an incrementally computed version of the LM-cut heuristic. The resulting algorithm for optimal delete-free planning exceeds the performance of A* with the LM-cut heuristic in the state-of-the-art planner Fast Downward. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.