@inproceedings{bb9e0876c36348429e47e687f4fc2986,
title = "An admissible HTN planning heuristic",
abstract = "Hierarchical task network (HTN) planning is wellknown for being an efficient planning approach. This is mainly due to the success of the HTN planning system SHOP2. However, its performance depends on hand-designed search control knowledge. At the time being, there are only very few domainindependent heuristics, which are designed for differing hierarchical planning formalisms. Here, we propose an admissible heuristic for standard HTN planning, which allows to find optimal solutions heuristically. It bases upon the so-called task decomposition graph (TDG), a data structure reflecting reachable parts of the task hierarchy. We show (both in theory and empirically) that rebuilding it during planning can improve heuristic accuracy thereby decreasing the explored search space. The evaluation further studies the heuristic both in terms of plan quality and coverage.",
author = "Pascal Bercher and Gregor Behnke and Daniel H{\"o}ller and Susanne Biundo",
year = "2017",
doi = "10.24963/ijcai.2017/68",
language = "English",
series = "IJCAI International Joint Conference on Artificial Intelligence",
publisher = "International Joint Conferences on Artificial Intelligence",
pages = "480--488",
editor = "Carles Sierra",
booktitle = "26th International Joint Conference on Artificial Intelligence, IJCAI 2017",
address = "United States",
note = "26th International Joint Conference on Artificial Intelligence, IJCAI 2017 ; Conference date: 19-08-2017 Through 25-08-2017",
}