Tractable Reasoning in First-Order Knowledge Bases with Disjunctive Information
Abstract
This work proposes a new methodology for establish-ing the tractability of a reasoning service that deals with expressive first-order knowledge bases. It consists of defining a logic that is weaker than classical logic and that has two properties: first, the entailment problem can be reduced to the model checking problem for a small number of characteristic models; and second, the model checking problem itself is tractable for formu-las with a bounded number of variables. We show this methodology in action for the reasoning service previ-ously proposed by Liu, Lakemeyer and Levesque for dealing with disjunctive information. They show that their reasoning is tractable in the propositional case and decidable in the first-order case. Here we apply the methodology and prove that the reasoning is also tractable in the first-order case if the knowledge base and the query both use a bounded number of variables.
Cite
Text
Liu and Levesque. "Tractable Reasoning in First-Order Knowledge Bases with Disjunctive Information." AAAI Conference on Artificial Intelligence, 2005.Markdown
[Liu and Levesque. "Tractable Reasoning in First-Order Knowledge Bases with Disjunctive Information." AAAI Conference on Artificial Intelligence, 2005.](https://mlanthology.org/aaai/2005/liu2005aaai-tractable/)BibTeX
@inproceedings{liu2005aaai-tractable,
title = {{Tractable Reasoning in First-Order Knowledge Bases with Disjunctive Information}},
author = {Liu, Yongmei and Levesque, Hector J.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2005},
pages = {639-644},
url = {https://mlanthology.org/aaai/2005/liu2005aaai-tractable/}
}