Hierarchical Task Network Planning with Task Insertion and State Constraints
Abstract
We extend hierarchical task network planning with task insertion (TIHTN) by introducing state constraints, called TIHTNS. We show that just as for TIHTN planning, all solutions of the TIHTNS planning problem can be obtained by acyclic decomposition and task insertion, entailing that its plan-existence problem is decidable without any restriction on decomposition methods. We also prove that the extension by state constraints does not increase the complexity of the plan-existence problem, which stays 2-NEXPTIME-complete, based on an acyclic progression operator. In addition, we show that TIHTNS planning covers not only the original TIHTN planning but also hierarchy-relaxed hierarchical goal network planning.
Cite
Text
Xiao et al. "Hierarchical Task Network Planning with Task Insertion and State Constraints." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/623Markdown
[Xiao et al. "Hierarchical Task Network Planning with Task Insertion and State Constraints." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/xiao2017ijcai-hierarchical/) doi:10.24963/IJCAI.2017/623BibTeX
@inproceedings{xiao2017ijcai-hierarchical,
title = {{Hierarchical Task Network Planning with Task Insertion and State Constraints}},
author = {Xiao, Zhanhao and Herzig, Andreas and Perrussel, Laurent and Wan, Hai and Su, Xiaoheng},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2017},
pages = {4463-4469},
doi = {10.24963/IJCAI.2017/623},
url = {https://mlanthology.org/ijcai/2017/xiao2017ijcai-hierarchical/}
}