On creating complementary pattern databases

Santiago Franco Aixela, Alvaro Torralba, Levi HS Lelis, Mike Barley

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

21 Citations (Scopus)


A pattern database (PDB) for a planning task is a heuristic function in the form of a lookup table that contains optimal solution costs of a simplified version of the task. In this paper we introduce a method that sequentially creates multiple PDBs which are later combined into a single heuristic function. At a given iteration, our method uses estimates of the A* running time to create a PDB that complements the strengths of the PDBs created in previous iterations. We evaluate our algorithm using explicit and symbolic PDBs. Our results show that the heuristics produced by our approach are able to outperform existing schemes, and that our method is able to create PDBs that complement the strengths of other existing heuristics such as a symbolic perimeter heuristic.
Original languageEnglish
Title of host publicationProceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17)
EditorsCarles Sierra
Number of pages8
ISBN (Electronic)9780999241103
Publication statusPublished - 1 Aug 2017
Event26th International Joint Conference on Artificial Intelligence - Melbourne Convention Centre, Melbourne, Australia
Duration: 19 Aug 201725 Aug 2017
Conference number: 26
https://ijcai-17.org/ (Link to Conference Website )


Conference26th International Joint Conference on Artificial Intelligence
Abbreviated titleIJCAI 2017
Internet address


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