Rational Inference Relations from Maximal Consistent Subsets Selection
Rational Inference Relations from Maximal Consistent Subsets Selection
Sébastien Konieczny, Pierre Marquis, Srdjan Vesic
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
Main track. Pages 1749-1755.
https://doi.org/10.24963/ijcai.2019/242
When one wants to draw non-trivial inferences from an inconsistent belief base, a very natural approach is to take advantage of the maximal consistent subsets of the base. But few inference relations from maximal consistent subsets exist. In this paper we point out new such relations based on selection of some of the maximal consistent subsets, leading thus to inference relations with a stronger inferential power. The selection process must obey some principles to ensure that it leads to an inference relation which is rational. We define a general class of monotonic selection relations for comparing maximal consistent sets. And we show that it corresponds to the class of rational inference relations.
Keywords:
Knowledge Representation and Reasoning: Non-monotonic Reasoning
Knowledge Representation and Reasoning: Non-classical Logics for Knowledge Representation