On the Parameterized Complexity of Belief Revision
Abstract
Parameterized complexity is a well recognized vehicle for understanding the multitude of complexity AI problems typically exhibit. However, the prominent problem of belief revision has not undergone a systematic investigation in this direction yet. This is somewhat surprising, since by its very nature of involving a knowledge base and a revision formula, this problem provides a perfect playground for investigating novel parameters. Among our results on the parameterized complexity of revision is thus a versatile fpt algorithm which is based on the parameter of the number of atoms shared by the knowledge base and the revision formula. Towards identifying the frontier between parameterized tractability and intractability, we also give hardness results for classes such as co-W[1], para-Theta2P and FPTNP[f(k)]
Cite
Text
Pfandler et al. "On the Parameterized Complexity of Belief Revision." International Joint Conference on Artificial Intelligence, 2015.Markdown
[Pfandler et al. "On the Parameterized Complexity of Belief Revision." International Joint Conference on Artificial Intelligence, 2015.](https://mlanthology.org/ijcai/2015/pfandler2015ijcai-parameterized/)BibTeX
@inproceedings{pfandler2015ijcai-parameterized,
title = {{On the Parameterized Complexity of Belief Revision}},
author = {Pfandler, Andreas and Rümmele, Stefan and Wallner, Johannes Peter and Woltran, Stefan},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2015},
pages = {3149-3155},
url = {https://mlanthology.org/ijcai/2015/pfandler2015ijcai-parameterized/}
}