Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning

Seipp, Jendrik. (2019) Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019). pp. 5621-5627.

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Official URL: https://edoc.unibas.ch/74972/

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Pattern databases are the foundation of some of the strongest admissible heuristics for optimal classical planning. Experiments showed that the most informative way of combining information from multiple pattern databases is to use saturated cost partitioning. Previous work selected patterns and computed saturated cost partitionings over the resulting pattern database heuristics in two separate steps. We introduce a new method that uses saturated cost partitioning to select patterns and show that it outperforms all existing pattern selection algorithms.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Artificial Intelligence (Helmert)
UniBasel Contributors:Seipp, Jendrik
Item Type:Conference or Workshop Item, refereed
Conference or workshop item Subtype:Conference Paper
Note:Publication type according to Uni Basel Research Database: Conference paper
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Last Modified:10 Mar 2020 13:41
Deposited On:10 Mar 2020 13:41

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