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How Potential BLFs Can Help to Decide Under Incomplete Knowledge

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications (IPMU 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 855))

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.

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Notes

  1. 1.

    Candidates are also called alternatives in the literature.

  2. 2.

    The agent’s knowledge K being considered to be certain, we write “\(\varphi \) holds” instead of “\(\varphi \) is believed to hold”.

  3. 3.

    The equivalence relation associated to \(\preceq \) is denoted \(\simeq \, (x \simeq y \Leftrightarrow x \preceq y\) and \(y\preceq x\)) and the strict order is denoted \(\prec \, ( x \prec y \Leftrightarrow x \preceq y\) and not \(y \preceq x\)).

  4. 4.

    Note that the set \(P\mathtt R\) is not meaningful in this context.

  5. 5.

    DNF: Disjunctive Normal Form.

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Authors and Affiliations

  1. IRIT, Université de Toulouse, Toulouse, France

    Florence Dupin de Saint-Cyr & Romain Guillaume

Authors
  1. Florence Dupin de Saint-Cyr
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  2. Romain Guillaume
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Corresponding author

Correspondence to Romain Guillaume .

Editor information

Editors and Affiliations

  1. Universidad de Cádiz, Cádiz, Cadiz, Spain

    Jesús Medina

  2. Universidad de Málaga, Málaga, Málaga, Spain

    Manuel Ojeda-Aciego

  3. Universidad de Granada, Granada, Spain

    José Luis Verdegay

  4. Institute for Research and Applications, University of Ostrava, Ostrava, Czech Republic

    Irina Perfilieva

  5. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  6. Iona College, New Rochelle, New York, USA

    Ronald R. Yager

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de Saint-Cyr, F.D., Guillaume, R. (2018). How Potential BLFs Can Help to Decide Under Incomplete Knowledge. In: Medina, J., Ojeda-Aciego, M., Verdegay, J., Perfilieva, I., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2018. Communications in Computer and Information Science, vol 855. Springer, Cham. https://doi.org/10.1007/978-3-319-91479-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-91479-4_8

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  • Print ISBN: 978-3-319-91478-7

  • Online ISBN: 978-3-319-91479-4

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