Revision by Comparison for Ranking Functions
Meliha Sezgin, Gabriele Kern-Isberner
Abstract
Revision by Comparison (RbC) is a non-prioritized belief revision mechanism on epistemic states that specifies constraints on the plausibility of an input sentence via a designated reference sentence, allowing for kind of relative belief revision. In this paper, we make the strategy underlying RbC more explicit and transfer the mechanism together with its intuitive strengths to a semi-quantitative framework based on ordinal conditional functions where a more elegant implementation of RbC is possible. We furthermore show that RbC can be realized as an iterated revision by so-called weak conditionals. Finally, we point out relations of RbC to credibility-limited belief revision, illustrating the versatility of RbC for advanced belief revision operations.
BibTeX
@inproceedings{ijcai2022p379,
title = {Revision by Comparison for Ranking Functions},
author = {Sezgin, Meliha and Kern-Isberner, Gabriele},
booktitle = {Proceedings of the Thirty-First International Joint Conference on
Artificial Intelligence, {IJCAI-22}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Lud De Raedt},
pages = {2734--2740},
year = {2022},
month = {7},
note = {Main Track},
doi = {10.24963/ijcai.2022/379},
url = {https://doi.org/10.24963/ijcai.2022/379},
}