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How Potential BLFs Can Help to Decide under Incomplete Knowledge

Dupin de Saint Cyr - Bannay, Florence and Guillaume, Romain How Potential BLFs Can Help to Decide under Incomplete Knowledge. (2018) In: International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018), 11 June 2018 - 15 June 2018 (Cadiz, Spain).

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Official URL: https://doi.org/10.1007/978-3-319-91479-4_8

Abstract

In a Bipolar Leveled Framework (BLF) [7], the comparison of two candidates is done on the basis of the decision principles and inhibitions which are validated given the available knowledge-bases associated with each candidate. This article defines a refinement of the rules for comparing candidates by using the potential-BLFs which can be built according to what could additionally be learned about the candidates. We also propose a strategy for selecting the knowledge to acquire in order to better discriminate between candidates.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to Springer editor. This papers appears in volume 855 of Communications in Computer and Information Science book series - CCIS ISBN 978-3-319-91478-7 ISSN: 1865-0929 The original PDF is available at: https://link.springer.com/chapter/10.1007/978-3-319-91479-4_8
HAL Id:hal-02319705
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited On:04 Oct 2019 14:06

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