Updating Knowledge Bases with Disjunctive Information
Abstract
It is well known that the minimal change principle was widely used in knowledge base updates. However, recent research has shown that conventional minimal change methods, eg. the PMA (Winslett 1988), are generally problematic for updating knowledge bases with disjunctive information. In this paper, we propose two different approaches to deal with this problem -- one is called the minimal change with exceptions (MCE), the other is called the minimal change with maximal disjunctive inclusions (MCD). The first method is syntax-based, while the second is modeltheoretic. We show that these two approaches are equivalent for propositional knowledge base updates, and the second method is also appropriate for first order knowledge base updates. We then prove that our new update approaches still satisfy the standard Katsuno and Mendelzon's update postulates. Introduction The knowledge base update problem has been widely studied in AI. It generally addresses the following question: given a kno...
Cite
Text
Zhang and Foo. "Updating Knowledge Bases with Disjunctive Information." AAAI Conference on Artificial Intelligence, 1996.Markdown
[Zhang and Foo. "Updating Knowledge Bases with Disjunctive Information." AAAI Conference on Artificial Intelligence, 1996.](https://mlanthology.org/aaai/1996/zhang1996aaai-updating/)BibTeX
@inproceedings{zhang1996aaai-updating,
title = {{Updating Knowledge Bases with Disjunctive Information}},
author = {Zhang, Yan and Foo, Norman Y.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {1996},
pages = {562-568},
url = {https://mlanthology.org/aaai/1996/zhang1996aaai-updating/}
}