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/}
}