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Measuring consistency gain and information loss in stepwise inconsistency resolution. (English) Zbl 1341.68256

Liu, Weiru (ed.), Symbolic and quantitative approaches to reasoning with uncertainty. 11th European conference, ECSQARU 2011, Belfast, UK, June 29 – July 1, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-22151-4/pbk). Lecture Notes in Computer Science 6717. Lecture Notes in Artificial Intelligence, 362-373 (2011).
Summary: Inconsistency is a usually undesirable feature of many kinds of data and knowledge. But altering the information in order to make it less inconsistent may result in the loss of information. In this paper we analyze this trade-off. We review some existing proposals and make new proposals for measures of inconsistency and information. We prove that in both cases the various measures are all pairwise incompatible. Then we introduce the concept of stepwise inconsistency resolution and show what happens in case an inconsistency resolution step applies a deletion, a weakening, or a splitting operation.
For the entire collection see [Zbl 1216.68033].

MSC:

68T37 Reasoning under uncertainty in the context of artificial intelligence
68T35 Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence
94A17 Measures of information, entropy
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References:

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