From arguments to constraints on a Bayesian network

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    Abstract

    In this paper, we propose a way to derive constraints for a Bayesian Network from structured arguments. Argumentation and Bayesian networks can both be considered decision support techniques, but are typically used by experts with different backgrounds. Bayesian network experts have the mathematical skills to understand and construct such networks, but lack expertise in the application domain; domain experts may feel more comfortable with argumentation approaches. Our proposed method allows us to check Bayesian networks given arguments constructed for the same problem, and also allows for transforming arguments into a Bayesian network structure, thereby facilitating Bayesian network construction.
    Original languageEnglish
    Title of host publicationComputational Models of Argument
    EditorsPietro Baroni, Thomas F. Gordon, Tatjana Scheffler, Manfred Stede
    PublisherIOS Press
    Pages95-106
    Number of pages12
    ISBN (Electronic)978-1-61499-686-6
    ISBN (Print)978-1-61499-685-9
    DOIs
    Publication statusPublished - 2016

    Publication series

    NameFrontiers in Artificial Intelligence and Applications
    PublisherIOS Press
    Volume287

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