@InProceedings{Lin2024HTNModelFixing,
  author    = {Songtuan Lin and Daniel H\"oller and Pascal Bercher},
  booktitle = {Proceedings of the 17th International Symposium on Combinatorial Search (SoCS 2024)},
  title     = {Modeling Assistance for Hierarchical Planning: An Approach for Correcting Hierarchical Domains with Missing Actions},
  note      = {<b><i>This paper won the SoCS 2024 Best Student Paper Award</i></b>},
  year      = {2024},
  publisher = {AAAI Press},
  doi       = {10.1609/socs.v17i1.31542},
  pages     = {55--63},
  abstract  = {The complexity of modeling planning domains is a major obstacle for making automated planning techniques more accessible, raising the demand of tools for providing modeling assistance. In particular, tools that can automatically correct errors in a planning domain are of great importance. Previous works have devoted efforts to developing such approaches for correcting classical (non-hierarchical) domains. However, no approaches exist for hierarchical planning, which is what we offer here. More specifically, our approach takes as input a flawed hierarchical domain together with a plan known to be a solution but actually contradicting the domain (due to errors in the domain) and outputs corrections to the domain that add missing actions to the domain and make the plan a solution. The approach achieves this by compiling the problem of finding corrections as another hierarchical planning problem.},
  url_Paper  = {https://bercher.net/publications/2024/Lin2024HTNModelFixing.pdf},
  url_Poster = {https://bercher.net/publications/2024/Lin2024HTNModelFixingPoster.pdf},
  url_Slides = {https://bercher.net/publications/2024/Lin2024HTNModelFixingSlides.pdf},
  url_zenodo = {https://zenodo.org/records/10946945},
  keywords   = {conference}
}

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