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T. Eiter, M. Fink, A. Weinzierl:
"Preference-Based Inconsistency Assessment in Multi-Context Systems";
Talk: 12th European Conference on Logics in Artificial Intelligence (JELIA 2010), Helsinki, Finland; 2010-09-13 - 2010-09-15; in: "12th European Conference on Logics in Artificial Intelligence (JELIA 2010)", T. Janhunen, I. Niemelä (ed.); Springer, 6341 (2010), ISBN: 978-3-642-15674-8; 143 - 155.

Resolving inconsistency in knowledge-integration systems is a major issue, especially when interlinking heterogeneous, autonomous sources. The latter can be done using a multi-context system, also in presence of non-monotonicity. Recent work considered diagnosis and explanation of inconsistency in such systems in terms of faulty information exchange. To discriminate between different solutions, we consider inconsistency assessment using preference. We present means to a) filter undesired diagnoses b) select the most preferred ones given an arbitrary preference order and c) use CP-nets for efficient selection. Furthermore, we show how to incorporate the assessment into a Multi-Context System by a transformational approach. In a range of settings, the complexity does not increase compared to the basic case and key properties like decentralized information exchange and information hiding are preserved.

Inconsistency Management, Multi-Context Systems, Hybrid Reasoning Systems, Nonmonotonic Reasoning, Preferences

http://dx.doi.org/10.1007/978-3-642-15675-5_14

Project Head Thomas Eiter:
Modulare HEX-Programme

Project Head Michael Fink:
Inconsistency Management for Knowledge-Integration Systems