Computing Superior Counter-Examples for Conformant Planning
Abstract
In a counter-example based approach to conformant planning, choosing the right counter-example can improve performance. We formalise this observation by introducing the notion of “superiority” of a counter-example over another one, that holds whenever the superior counter-example exhibits more tags than the latter. We provide a theoretical explanation that supports the strategy of searching for maximally superior counter-examples, and we show how this strategy can be implemented. The empirical experiments validate our approach.
Cite
Text
Zhang et al. "Computing Superior Counter-Examples for Conformant Planning." AAAI Conference on Artificial Intelligence, 2020. doi:10.1609/AAAI.V34I06.6558Markdown
[Zhang et al. "Computing Superior Counter-Examples for Conformant Planning." AAAI Conference on Artificial Intelligence, 2020.](https://mlanthology.org/aaai/2020/zhang2020aaai-computing-a/) doi:10.1609/AAAI.V34I06.6558BibTeX
@inproceedings{zhang2020aaai-computing-a,
title = {{Computing Superior Counter-Examples for Conformant Planning}},
author = {Zhang, Xiaodi and Grastien, Alban and Scala, Enrico},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2020},
pages = {10017-10024},
doi = {10.1609/AAAI.V34I06.6558},
url = {https://mlanthology.org/aaai/2020/zhang2020aaai-computing-a/}
}