Preference-Based Inconsistency Management in Multi-Context Systems

Authors: Thomas Eiter, Antonius Weinzierl

JAIR 2017 | Venue PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical Our main contributions are briefly summarized as follows: We propose two basic methods for selection of preferred diagnoses: one allows to filter out diagnoses that fail some properties (similar to hard constraints); the other method compares diagnoses with each other in a binary relation and identifies the most preferred one(s). ... We investigate the computational complexity of these notions and show by polynomial-time reductions that the first two are of the same complexity as checking whether a pair of sets of bridge rules constitutes a subset-minimal diagnosis.
Researcher Affiliation Academia Thomas Eiter EMAIL Technische Universität Wien Institut für Informationssysteme Abteilung für Wissensbasierte Systeme Favoritenstr. 9-11, 184/3 1040 Vienna, Austria Antonius Weinzierl EMAIL Aalto University Department of Computer Science Konemiehentie 2 02150 Espoo, Finland
Pseudocode Yes Algorithm 1: Deciding whether (D1, D2) ∈ Dm,tmax (M, br P , br H) holds. Input : MCS M, (D1, D2), br P , and br H with D1, D2 ⊆ br(M), br P , br H ⊆ br(M). Output: YES if (D1, D2) ∈ Dm,tmax (M, br P , br H)
Open Source Code No No explicit statement of code release for the methodology described in this paper is provided. The paper mentions existing tools/frameworks like 'MCS-IE tool by Bögl et al. (2010) and Eiter et al. (2014)' and 'encoding the diagnoses of an MCS to answer sets of a HEX-program as in the work of Eiter et al. (2010)' which are third-party or previous work, not code released for this specific research.
Open Datasets No The paper focuses on theoretical concepts, formalisms, and computational complexity within Multi-Context Systems (MCS). It does not describe any experiments that use specific datasets. Therefore, there is no mention of publicly available datasets or access information for them.
Dataset Splits No The paper is theoretical and focuses on computational complexity and formal methods for inconsistency management in Multi-Context Systems. It does not involve experimental evaluation with datasets, and thus, no dataset splits are described.
Hardware Specification No The paper is theoretical, focusing on formal methods and computational complexity for inconsistency management in Multi-Context Systems. It does not describe any experimental setup or report results obtained from running experiments on specific hardware.
Software Dependencies No The paper introduces formalisms and analyzes computational complexity. While it mentions concepts like 'ASP semantics' and 'HEX-program' in the context of theoretical discussions or related work, it does not specify any software dependencies with version numbers for reproducing its own contributions or results.
Experiment Setup No The paper focuses on theoretical research, developing formal methods and analyzing computational complexity for inconsistency management in Multi-Context Systems. It does not describe any empirical experiments or their setup, thus no hyperparameter values, training configurations, or system-level settings are provided.