{"type":"ScholarlyArticle","title":"On Guiding Search in HTN Planning with Classical Planning Heuristics","authors":[{"name":"Daniel Höller","slug":"daniel-holler","given":"Daniel","family":"Höller","affiliation":"Institute of Artificial Intelligence , Ulm University , Germany"},{"name":"Pascal Bercher","slug":"pascal-bercher","given":"Pascal","family":"Bercher","affiliation":"Institute of Artificial Intelligence , Ulm University , Germany"},{"name":"Gregor Behnke","slug":"gregor-behnke","given":"Gregor","family":"Behnke","affiliation":"Institute of Artificial Intelligence , Ulm University , Germany"},{"name":"Susanne Biundo","slug":"susanne-biundo","given":"Susanne","family":"Biundo","affiliation":"Institute of Artificial Intelligence , Ulm University , Germany"}],"abstract":"Planning is the task of finding a sequence of actions that achieves the goal(s) of an agent. It is solved based on a model describing the environment and how to change it. There are several approaches to solve planning tasks, two of the most popular are classical planning and hierarchical planning. Solvers are often based on heuristic search, but especially regarding domain-independent heuristics, techniques in classical planning are more sophisticated. However, due to the different problem classes, it is difficult to use them in hierarchical planning. In this paper we describe how to use arbitrary classical heuristics in hierarchical planning and show that the resulting system outperforms the state of the art in hierarchical planning.","doi":"10.24963/ijcai.2019/857","url":"https://ijcai.org/proceedings/2019/857","pdf":"https://ijcai.org/proceedings/2019/0857.pdf","markdown":"https://ijcai.org/proceedings/2019/857.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/857","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Best Sister Conferences","track":"Best Sister Conferences","number":857,"pages":{"first":6171,"last":6175},"keywords":["Planning and Scheduling: Planning Algorithms","Planning and Scheduling: Hierarchical planning","Planning and Scheduling: Search in Planning and Scheduling"],"videos":[],"references":[{"position":1,"raw":"[Alford et al., 2009] Ronald Alford, Ugur Kuter, and Dana S. 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