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Rough Set Approach to Decisions under Risk

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Rough Sets and Current Trends in Computing (RSCTC 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2005))

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Abstract

In this paper we open a new avenue for applications of the rough set concept to decision support. We consider the classical problem of decision under risk proposing a rough set model based on stochastic dominance. We start with the case of traditional additive probability distribution over the set of states of the world, however, the model is rich enough to handle non-additive probability distributions and even qualitative ordinal distributions. The rough set approach gives a representation of decision maker’s preferences in terms of “if..., then...” decision rules induced from rough approximations of sets of exemplary decisions.

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References

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Author information

Authors and Affiliations

  1. Faculty of Economics, University of Catania, 95129, Catania, Italy

    S. Greco

  2. Institute of Computing Science, Poznan University of Technology, 60965, Poznan, Poland

    B. Matarazzo & R. Slowinski

Authors
  1. S. Greco
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  2. B. Matarazzo
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  3. R. Slowinski
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina Regina, S4S 0A2, Saskatchewan, Canada

    Wojciech Ziarko  & Yiyu Yao  & 

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© 2001 Springer-Verlag Berlin Heidelberg

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Greco, S., Matarazzo, B., Slowinski, R. (2001). Rough Set Approach to Decisions under Risk. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_19

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  • DOI: https://doi.org/10.1007/3-540-45554-X_19

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43074-2

  • Online ISBN: 978-3-540-45554-7

  • eBook Packages: Springer Book Archive

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