Elicitation of sugeno integrals: A version space learning perspective

Publication Type:
Conference Proceeding
Citation:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, 5722 LNAI pp. 392 - 401
Issue Date:
2009-10-16
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Sugeno integrals can be viewed as multiple criteria aggregation functions which take into account a form of synergy between criteria. As such, Sugeno integrals constitute an important family of tools for modeling qualitative preferences defined on ordinal scales. The elicitation of Sugeno integrals starts from a set of data that associates a global evaluation assessment to situations described by multiple criteria values. A consistent set of data corresponds to a non-empty family of Sugeno integrals with which the data are compatible. This elicitation process presents some similarity with the revision process underlying the version space approach in concept learning, when new data are introduced. More precisely, the elicitation corresponds to a graded extension of version space learning, recently proposed in the framework of bipolar possibility theory. This paper establishes the relation between these two formal settings. © 2009 Springer Berlin Heidelberg.
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