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Sequential Decision Process Supported by a Compositional Model

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9978))

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Abstract

The goal of the paper is to describe a classical sequential decision process that is often used for both medical and technical diagnosis making in a relatively new theoretical setting. For this, we represent the background knowledge, which is assumed to be expressed in the form of a multidimensional probability distribution, as a compositional model. Though we do not perform a detailed analysis of its computational complexity, we show that the whole process is easily tractable for probability distributions of very high dimensions in the case that the distribution is represented as a compositional model of special properties.

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Acknowledgement

This research was partially supported by GAČR under Grant No. 15-00215S.

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Authors and Affiliations

  1. Faculty of Management, University of Economics, Jindřichův Hradec, Czech Republic

    Radim Jiroušek & Lucie Váchová

  2. Institute of Information Theory and Automation, Czech Academy of Sciences, Prague, Czech Republic

    Radim Jiroušek

Authors
  1. Radim Jiroušek
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  2. Lucie Váchová
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Corresponding author

Correspondence to Radim Jiroušek .

Editor information

Editors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Van-Nam Huynh

  2. Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan

    Masahiro Inuiguchi

  3. University of Science, Ho Chi Minh City, Vietnam

    Bac Le

  4. Duy Tan University, Da Nang, Vietnam

    Bao Nguyen Le

  5. Université de Technologie de Compiègne , Compiègne, France

    Thierry Denoeux

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Jiroušek, R., Váchová, L. (2016). Sequential Decision Process Supported by a Compositional Model. In: Huynh, VN., Inuiguchi, M., Le, B., Le, B., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2016. Lecture Notes in Computer Science(), vol 9978. Springer, Cham. https://doi.org/10.1007/978-3-319-49046-5_5

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  • DOI: https://doi.org/10.1007/978-3-319-49046-5_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49045-8

  • Online ISBN: 978-3-319-49046-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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