Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning

Seipp, Jendrik

doi:10.24963/ijcai.2019/780

Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning

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Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence. Main track. Pages 5621-5627.

https://doi.org/10.24963/ijcai.2019/780

Keywords

Planning and Scheduling: Planning and Scheduling
Planning and Scheduling: Search in Planning and Scheduling

Abstract

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.

Jendrik Seipp. 2019. Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19. IJCAI, 5621–5627. https://doi.org/10.24963/ijcai.2019/780

@inproceedings{ijcai2019p780,
  title     = {Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning},
  author    = {Seipp, Jendrik},
  booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on
               Artificial Intelligence, {IJCAI-19}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Sarit Kraus},
  pages     = {5621--5627},
  year      = {2019},
  month     = {8},
  note      = {Main track},
  doi       = {10.24963/ijcai.2019/780},
  url       = {https://doi.org/10.24963/ijcai.2019/780},
}

TY  - CPAPER
TI  - Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning
AU  - Seipp, Jendrik
T2  - Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2019
SP  - 5621
EP  - 5627
DO  - 10.24963/ijcai.2019/780
UR  - https://doi.org/10.24963/ijcai.2019/780
ER  -