Preference-Based Inconsistency Management in Multi-Context Systems (Extended Abstract)

Thomas Eiter, Antonius Weinzierl

Research output: Contribution to conferenceAbstractScientificpeer-review


Establishing information exchange between existing knowledge-based systems can lead to devastating inconsistency. Automatic resolution of inconsistency often is unsatisfactory, because any modification of the information flow may lead to bad or even dangerous conclusions. Methods to identify and select preferred repairs of inconsistency are thus needed. In this work, we leverage the expressive power and generality of Multi-Context Systems (MCS), a formalism for information exchange, to select most preferred repairs, by use of a meta-reasoning transformation. As for computational complexity, finding preferred repairs is not higher than the base case; finding most-preferred repairs is higher, yet worst-case optimal.
Original languageEnglish
Number of pages5
Publication statusPublished - 2018
EventInternational Joint Conference on Artificial Intelligence - Stockholm, Sweden
Duration: 13 Jul 201819 Jul 2018
Conference number: 27


ConferenceInternational Joint Conference on Artificial Intelligence
Abbreviated titleIJCAI
Internet address


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