Planning with Multi-Valued Landmarks
Abstract
Landmark heuristics are perhaps the most accurate current known admissible heuristics for optimal planning. A disjunctive action landmark can be seen a form of at-least-one constraint on the actions it contains. In many domains, some critical propositions have to be established for a number of times.Propositional landmarks are too weak to express this kind of constraints.In this paper, we propose to generalize landmarks to multi-valued landmarks to represent the more general cardinality constraints. We present a class of local multi-valued landmarks that can be efficiently extracted from propositional landmarks.By encoding multi-valued landmarks into CNF formulas, we can also use SAT solvers to systematically extract multi-valued landmarks.Experiment evaluations show that multi-valued landmark based heuristics are more close to $h^*$ andcompete favorably with the state-of-the-art of admissible landmark heuristics on benchmark domains.
Cite
Text
Zhang et al. "Planning with Multi-Valued Landmarks." AAAI Conference on Artificial Intelligence, 2013. doi:10.1609/AAAI.V27I1.8520Markdown
[Zhang et al. "Planning with Multi-Valued Landmarks." AAAI Conference on Artificial Intelligence, 2013.](https://mlanthology.org/aaai/2013/zhang2013aaai-planning/) doi:10.1609/AAAI.V27I1.8520BibTeX
@inproceedings{zhang2013aaai-planning,
title = {{Planning with Multi-Valued Landmarks}},
author = {Zhang, Lei and Wang, Chong-Jun and Wu, Jun and Liu, Meilin and Xie, Jun-Yuan},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2013},
pages = {1653-1654},
doi = {10.1609/AAAI.V27I1.8520},
url = {https://mlanthology.org/aaai/2013/zhang2013aaai-planning/}
}