Name
Abstract | ||
|---|---|---|
We address the issue of quantitatively assessing the severity of inconsistencies in non-monotonic frameworks. While measuring inconsistency in classical logics has been investigated for some time now, taking the non-monotonicity into account poses new challenges. In order to tackle them, we focus on the structure of minimal strongly K-inconsistent subsets of a knowledge base K—a sound generalization of minimal inconsistent subsets to arbitrary, possibly non-monotonic, frameworks which induces a generalization of Reiter's famous hitting set duality between minimal inconsistent and maximal consistent subsets of a knowledge base. We propose measures based on this notion and investigate their behavior in a non-monotonic setting by revisiting existing rationality postulates, analyzing the compliance of the proposed measures with these postulates, and by investigating their computational complexity. Motivated by the observation that a knowledge base of a non-monotonic logic can also be repaired by adding formulas – whereas Reiter's duality is only concerned about removing –, we also investigate situations where we are given potential additional assumptions to repair a knowledge base. For this, we characterize the minimal modifications to a knowledge base in terms of a hitting set duality |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.artint.2020.103344 | Artificial Intelligence |
Keywords | DocType | Volume |
Non-monotonic reasoning,Inconsistency handling,Inconsistency measurement | Journal | 286 |
Issue | ISSN | Citations |
1 | 0004-3702 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Markus Ulbricht | 1 | 1 | 7.10 |
| Matthias Thimm | 2 | 574 | 58.87 |
| Gerhard Brewka | 3 | 2529 | 183.64 |