ML Anthology

On Succinct Groundings of HTN Planning Problems

Gregor Behnke, Daniel Höller, Alexander Schmid, Pascal Bercher, Susanne Biundo
AAAI 2020 pp. 9775-9784
doi:10.1609/AAAI.V34I06.6529 /aaai/2020/behnke2020aaai-succinct/

Abstract

Both search-based and translation-based planning systems usually operate on grounded representations of the problem. Planning models, however, are commonly defined using lifted description languages. Thus, planning systems usually generate a grounded representation of the lifted model as a preprocessing step. For HTN planning models, only one method to ground lifted models has been published so far. In this paper we present a new approach for grounding HTN planning problems that produces smaller groundings in a shorter timespan than the previously published method.

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Text

Behnke et al. "On Succinct Groundings of HTN Planning Problems." AAAI Conference on Artificial Intelligence, 2020. doi:10.1609/AAAI.V34I06.6529

Markdown

[Behnke et al. "On Succinct Groundings of HTN Planning Problems." AAAI Conference on Artificial Intelligence, 2020.](https://mlanthology.org/aaai/2020/behnke2020aaai-succinct/) doi:10.1609/AAAI.V34I06.6529

BibTeX

@inproceedings{behnke2020aaai-succinct,
  title     = {{On Succinct Groundings of HTN Planning Problems}},
  author    = {Behnke, Gregor and Höller, Daniel and Schmid, Alexander and Bercher, Pascal and Biundo, Susanne},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2020},
  pages     = {9775-9784},
  doi       = {10.1609/AAAI.V34I06.6529},
  url       = {https://mlanthology.org/aaai/2020/behnke2020aaai-succinct/}
}