Resolving Conflicting Arguments Under Uncertainties
Abstract
Distributed knowledge based applications in open domain rely on common sense information which is bound to be uncertain and incomplete. To draw the useful conclusions from ambiguous data, one must address uncertainties and conflicts incurred in a holistic view. No integrated frameworks are viable without an in-depth analysis of conflicts incurred by uncertainties. In this paper, we give such an analysis and based on the result, propose an integrated framework. Our framework extends definite argumentation theory to model uncertainty. It supports three views over conflicting and uncertain knowledge. Thus, knowledge engineers can draw different conclusions depending on the application context (i.e. view). We also give an illustrative example on strategical decision support to show the practical usefulness of our framework.
Cite
Text
Ng et al. "Resolving Conflicting Arguments Under Uncertainties." Conference on Uncertainty in Artificial Intelligence, 1998.Markdown
[Ng et al. "Resolving Conflicting Arguments Under Uncertainties." Conference on Uncertainty in Artificial Intelligence, 1998.](https://mlanthology.org/uai/1998/ng1998uai-resolving/)BibTeX
@inproceedings{ng1998uai-resolving,
title = {{Resolving Conflicting Arguments Under Uncertainties}},
author = {Ng, Benson Hin Kwong and Wong, Kam-Fai and Low, Boon Toh},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1998},
pages = {414-421},
url = {https://mlanthology.org/uai/1998/ng1998uai-resolving/}
}