Abstract: We introduce the metric induced by Gaifman graphs into lifted planning. We analyze what kind of information this metric carries and how it can be utilized for constructing lifted delete-free relaxation heuristics. In particular, we prove how the action dynamics influence the distances between objects. As a corollary, we derive a lower bound on the length of any plan. Finally, we apply our theoretical findings on the Gaifman graphs to improve the delete-free relaxation heuristics induced by PDDL homomorphisms.
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