Strengthening Landmark Heuristics via Hitting Sets

The landmark cut heuristic is perhaps the strongest known polytime admissible approximation of the optimal delete relaxation heuristic h+ . Equipped with this heuristic, a best-first search was able to optimally solve 40% more benchmark problems than the winners of the sequential optimization track of IPC 2008. We show that this heuristic can be understood as a simple relaxation of a hitting set problem, and that stronger heuristics can be obtained by considering stronger relaxations. Based on these findings, we propose a simple polytime method for obtaining heuristics stronger than landmark cut, and evaluate them over benchmark problems. We also show that hitting sets can be used to characterize h+ and thus provide a fresh and novel insight for better comprehension of the delete relaxation.

• Type: Conference
• Year: 2010
• Where: ECAI
• Authors: Blai Bonet, Malte Helmert
• Keywords: Artificial Intelligence, Delete Relaxation, ECAI 2010, Heuristics, Relaxation Heuristic H+