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Refining a Heuristic for Constructing Bayesian Networks from Structured Arguments

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Artificial Intelligence (BNAIC 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 823))

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Abstract

Recently, a heuristic was proposed for constructing Bayesian networks (BNs) from structured arguments. This heuristic helps domain experts who are accustomed to argumentation to transform their reasoning into a BN and subsequently weigh their case evidence in a probabilistic manner. While the underlying undirected graph of the BN is automatically constructed by following the heuristic, the arc directions are to be set manually by a BN engineer in consultation with the domain expert. As the knowledge elicitation involved is known to be time-consuming, it is of value to (partly) automate this step. We propose a refinement of the heuristic to this end, which specifies the directions in which arcs are to be set given specific conditions on structured arguments.

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Notes

  1. 1.

    The terms ‘node’ and ‘variable’ are used interchangeably.

  2. 2.

    In figures in this paper, circles are used in BN graphs, rectangles are used in argument graphs and rounded rectangles are used in SGs. Nodes and propositions corresponding to evidence are shaded. Capital letters are used for the nodes in BN graphs and SGs, and lowercase letters are used for propositions.

  3. 3.

    The prime symbol is used to denote objects which result from applying the support graph method.

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Author information

Authors and Affiliations

  1. Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands

    Remi Wieten, Floris Bex, Linda C. van der Gaag, Henry Prakken & Silja Renooij

  2. Faculty of Law, University of Groningen, Groningen, The Netherlands

    Henry Prakken

Authors
  1. Remi Wieten
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  2. Floris Bex
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  3. Linda C. van der Gaag
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  4. Henry Prakken
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  5. Silja Renooij
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Corresponding author

Correspondence to Remi Wieten .

Editor information

Editors and Affiliations

  1. Artificial Intelligence, University of Groningen, Groningen, The Netherlands

    Bart Verheij

  2. Artificial Intelligence, University of Groningen, Groningen, The Netherlands

    Marco Wiering

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Wieten, R., Bex, F., van der Gaag, L.C., Prakken, H., Renooij, S. (2018). Refining a Heuristic for Constructing Bayesian Networks from Structured Arguments. In: Verheij, B., Wiering, M. (eds) Artificial Intelligence. BNAIC 2017. Communications in Computer and Information Science, vol 823. Springer, Cham. https://doi.org/10.1007/978-3-319-76892-2_3

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  • DOI: https://doi.org/10.1007/978-3-319-76892-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76891-5

  • Online ISBN: 978-3-319-76892-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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