Classifying inconsistency measures using graphs

G De Bona, J Grant, A Hunter, S Konieczny - Journal of Artificial Intelligence …, 2019 - jair.org
The aim of measuring inconsistency is to obtain an evaluation of the imperfections in a set of
formulas, and this evaluation may then be used to help decide on some course of action …

[HTML][HTML] Reactive multi-context systems: Heterogeneous reasoning in dynamic environments

G Brewka, S Ellmauthaler, R Gonçalves, M Knorr… - Artificial Intelligence, 2018 - Elsevier
Managed multi-context systems (mMCSs) allow for the integration of heterogeneous
knowledge sources in a modular and very general way. They were, however, mainly …

[HTML][HTML] Semantic inconsistency measures using 3-valued logics

J Grant, A Hunter - International Journal of Approximate Reasoning, 2023 - Elsevier
AI systems often need to deal with inconsistencies. One way of getting information about
inconsistencies is by measuring the amount of information in the knowledgebase. In the past …

Semantic data management in P2P systems driven by self-esteem

L Caroprese, E Zumpano - Journal of Logic and Computation, 2022 - academic.oup.com
This paper is a contribution to semantic data management in P2P systems. It is based on the
previous works of the same authors in which a declarative semantics for P2P systems is …

[HTML][HTML] Intrinsic approaches to prioritizing diagnoses in multi-context systems

K Mu - Artificial Intelligence, 2020 - Elsevier
Multi-context systems introduced by Brewka and Eiter provide a promising framework for
interlinking heterogeneous and autonomous knowledge sources. The notion of diagnosis …

Fuzzy Multicontext Systems

L Yang, YS Wang, HB Hu, RY Feng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Multicontext systems provide an effective representation and reasoning framework for
integrating heterogeneous knowledge obtained from different sources and have been …

Preference-based inconsistency management in multi-context systems

T Eiter, A Weinzierl - Journal of Artificial Intelligence Research, 2017 - jair.org
Multi-Context Systems (MCS) are a powerful framework for interlinking possibly
heterogeneous, autonomous knowledge bases, where information can be exchanged …

Multi-context system for optimization problems

T Le, TC Son, E Pontelli - Proceedings of the AAAI Conference on …, 2019 - ojs.aaai.org
This paper proposes Multi-context System for Optimization Problems (MCS-OP) by
introducing conditional costassignment bridge rules to Multi-context Systems (MCS). This …

Classifying Inconsistency Measures Using Graphs

A Hunter, G De Bona, J Grant… - Journal of Artificial …, 2019 - discovery.ucl.ac.uk
The aim of measuring inconsistency is to obtain an evaluation of the imperfections in a set of
formulas, and this evaluation may then be used to help decide on some course of action …

A Causality-Based Approach to Assessing Inconsistency for Multi-context Systems

K Mu - … : 12th International Conference, KSEM 2019, Athens …, 2019 - Springer
Nonmonotonic multi-context systems provide a promising starting point to interlink
heterogeneous and decentralized knowledge contexts effectively by modeling the …