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Planning Based on Decision Theory pp 3–26Cite as

Qualitative Decision Rules Under Uncertainty

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Part of the book series: International Centre for Mechanical Sciences ((CISM,volume 472))

Abstract

This paper is a survey of qualitative decision theory focusing on available decision rules under uncertainty, and their properties. It is pointed out that two main approaches exist according to whether degrees of uncertainty and degrees of utility are commensurate (that is, belong to a unique scale) or not. Savage-like axiom systems for both approaches are surveyed. In such a framework, acts are functions from states to results, and decision rules are derived from first principles, bearing on a preference relation on acts. It is shown that the emerging uncertainty theory in qualitative settings is possibility theory rather than probability theory. However these approaches lead to criteria that are either little decisive due to incomparability, or too adventurous because focusing on the most plausible states, or yet lacking discrimination because or the coarseness of the value scale. Some suggestions to overcome these defects are pointed out.

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Author information

Authors and Affiliations

  1. IRIT-CNRS, Université Paul Sabatier, Toulouse, France

    Didier Dubois & Hélène Fargier

Authors
  1. Didier Dubois
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  2. Hélène Fargier
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Editors and Affiliations

  1. University of Udine, Italy

    Giacomo Della Riccia

  2. University of Toulouse, France

    Didier Dubois

  3. University of Magdeburg, Germany

    Rudolf Kruse

  4. Free University of Berlin, Germany

    Hans-J. Lenz

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© 2003 Springer-Verlag Wien

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Dubois, D., Fargier, H. (2003). Qualitative Decision Rules Under Uncertainty. In: Della Riccia, G., Dubois, D., Kruse, R., Lenz, HJ. (eds) Planning Based on Decision Theory. International Centre for Mechanical Sciences, vol 472. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2530-4_1

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  • DOI: https://doi.org/10.1007/978-3-7091-2530-4_1

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-40756-1

  • Online ISBN: 978-3-7091-2530-4

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