Measuring the Good and the Bad in Inconsistent Information
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2632-2636.
Abstract
There is interest in artificial intelligence for principled techniques to analyze inconsistent information. This stems from the recognition that the dichotomy between consistent and inconsistent sets of formulae that comes from classical logics is not sufficient for describing inconsistent information. We review some existing proposals and make new proposals for measures of inconsistency and measures of information, and then prove that they are all pairwise incompatible. This shows that the notion of inconsistency is a multi-dimensional concept where different measures provide different insights. We then explore relationships between measures of inconsistency and measures of information in terms of the trade-offs they identify when using them to guide resolution of inconsistency.
@inproceedings{ijcai2011p438,
title = {Measuring the Good and the Bad in Inconsistent Information},
author = {Grant, John and Hunter, Anthony},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {2632--2636},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-438},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-438},
}
TY - CPAPER TI - Measuring the Good and the Bad in Inconsistent Information AU - Grant, John AU - Hunter, Anthony T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 2632 EP - 2636 DO - 10.5591/978-1-57735-516-8/IJCAI11-438 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-438 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
