Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning

IJCAI 2019 pp. 5621-5627

doi:10.24963/IJCAI.2019/780 /ijcai/2019/seipp2019ijcai-pattern/

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.

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Text

Seipp. "Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning." International Joint Conference on Artificial Intelligence, 2019. doi:10.24963/IJCAI.2019/780

Markdown

[Seipp. "Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning." International Joint Conference on Artificial Intelligence, 2019.](https://mlanthology.org/ijcai/2019/seipp2019ijcai-pattern/) doi:10.24963/IJCAI.2019/780

BibTeX

@inproceedings{seipp2019ijcai-pattern,
  title     = {{Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning}},
  author    = {Seipp, Jendrik},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2019},
  pages     = {5621-5627},
  doi       = {10.24963/IJCAI.2019/780},
  url       = {https://mlanthology.org/ijcai/2019/seipp2019ijcai-pattern/}
}