HTN Plan Repair via Model Transformation

HTN Plan Repair via Model Transformation. Höller, D., Bercher, P., Behnke, G., & Biundo, S. In Proceedings of the 43th German Conference on Artificial Intelligence (KI 2020), pages 88–101, 2020. Springer. This paper was nominated for the KI 2020 Best Paper Award

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To make planning feasible, planning models abstract from many details of the modeled system. When executing plans in the actual system, the model might be inaccurate in a critical point, and plan execution may fail. There are two options to handle this case: the previous solution can be modified to address the failure (plan repair), or the planning process can be re-started from the new situation (re-planning). In HTN planning, discarding the plan and generating a new one from the novel situation is not easily possible, because the HTN solution criteria make it necessary to take already executed actions into account. Therefore all approaches to repair plans in the literature are based on specialized algorithms. In this paper, we discuss the problem in detail and introduce a novel approach that makes it possible to use unchanged, off-the-shelf HTN planning systems to repair broken HTN plans. That way, no specialized solvers are needed.

@InProceedings{Hoeller2020HTNPlanRepair,
  author    = {Daniel H\"oller and Pascal Bercher and Gregor Behnke and Susanne Biundo},
  title     = {HTN Plan Repair via Model Transformation},
  booktitle = {Proceedings of the 43th German Conference on Artificial Intelligence ({KI} 2020)},
  year      = {2020},
  publisher = {Springer},
  pages     = {88--101},
  note      = {<b><i>This paper was nominated for the KI 2020 Best Paper Award</i></b>},
  abstract  = {To make planning feasible, planning models abstract from many details of the modeled system. When executing plans in the actual system, the model might be inaccurate in a critical point, and plan execution may fail. There are two options to handle this case: the previous solution can be modified to address the failure (plan repair), or the planning process can be re-started from the new situation (re-planning). In HTN planning, discarding the plan and generating a new one from the novel situation is not easily possible, because the HTN solution criteria make it necessary to take already executed actions into account. Therefore all approaches to repair plans in the literature are based on specialized algorithms. In this paper, we discuss the problem in detail and introduce a novel approach that makes it possible to use unchanged, off-the-shelf HTN planning systems to repair broken HTN plans. That way, no specialized solvers are needed.},
  doi       = {10.1007/978-3-030-58285-2_7},
  url_Paper = {https://bercher.net/publications/2020/Hoeller2020HTNRepair.pdf},
  keywords  = {conference}
}

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