Landmark Heuristics for Lifted Planning – Extended Abstract

Proceedings of the International Symposium on Combinatorial Search, 14

Volume

Vol. 14 No. 1 (2021): Fourteenth International Symposium on Combinatorial Search

Student Papers

Planning problems are usually modeled using lifted representations, they specify predicates and action schemas using variables over a finite universe of objects. However, current planning systems like Fast Downward need a grounded (propositional) input model. The process of grounding might result in an exponential blowup of the model size. This limits the application of grounded planning systems in practical applications. Recent work introduced an efficient planning system for lifted heuristic search, but the work on lifted heuristics is still limited. In this extended abstract, we introduce a novel lifted heuristic based on landmarks, which we extract from the lifted problem representation. Preliminary results on a benchmark set specialized to lifted planning show that there are domains where our approach finds enough landmarks to guide the search more effective than the heuristics available.

10.1609/socs.v12i1.18597