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Multiperson Decision Making Models Using Fuzzy Sets and Possibility Theory

  • Janusz Kacprzyk
  • Mario Fedrizzi

Part of the Theory and Decision Library book series (TDLB, volume 18)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Introductory Sections

    1. Front Matter
      Pages 1-1
    2. Vilém Novák
      Pages 28-42
    3. Hannu Nurmi, Mario Fedrizzi, Janusz Kacprzyk
      Pages 43-52
  3. General Issues Related to Decision Making under Fuzziness

    1. Front Matter
      Pages 53-53
    2. Didier Dubois, Henri Prade
      Pages 55-63
    3. Sergei Ovchinnikov
      Pages 64-70
    4. O. N. Bondareva
      Pages 71-79
    5. Vladimir B. Gisin
      Pages 80-89
    6. Livia D’Apuzzo, Massimo Squillante, Aldo G. S. Ventre
      Pages 98-104
    7. Ricardo José Machado, Armando Freitas da Rocha, Beatriz de Faria Leão
      Pages 113-127
  4. Group Decision Making under Fuzziness

  5. Team Decision Making under Fuzziness

    1. Front Matter
      Pages 253-253
    2. T. Whalen, C. Brönn
      Pages 267-285
  6. Fuzzy Games

    1. Front Matter
      Pages 287-287
    2. M. Delgado, J. L. Verdegay, M. A. Vila
      Pages 298-310
    3. G. Pederzoli, B. Viscolani
      Pages 336-341
  7. Back Matter
    Pages 343-346

About this book

Introduction

Decision making is certainly a very crucial component of many human activities. It is, therefore, not surprising that models of decisions play a very important role not only in decision theory but also in areas such as operations Research, Management science, social Psychology etc . . The basic model of a decision in classical normative decision theory has very little in common with real decision making: It portrays a decision as a clear-cut act of choice, performed by one individual decision maker and in which states of nature, possible actions, results and preferences are well and crisply defined. The only compo­ nent in which uncertainty is permitted is the occurence of the different states of nature, for which probabilistic descriptions are allowed. These probabilities are generally assumed to be known numerically, i. e. as single probabili­ ties or as probability distribution functions. Extensions of this basic model can primarily be conceived in three directions: 1. Rather than a single decision maker there are several decision makers involved. This has lead to the areas of game theory, team theory and group decision theory. 2. The preference or utility function is not single valued but rather vector valued. This extension is considered in multiattribute utility theory and in multicritieria analysis. 3.

Keywords

Change decision making economy fuzzy games fuzzy sets modeling

Editors and affiliations

  • Janusz Kacprzyk
    • 1
  • Mario Fedrizzi
    • 2
  1. 1.Systems Research InstitutePolish Academy of ScienceWarsawPoland
  2. 2.Institute of Computer ScienceUniversity of TrentoItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-009-2109-2
  • Copyright Information Springer Science+Business Media B.V. 1990
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-010-7448-3
  • Online ISBN 978-94-009-2109-2
  • Buy this book on publisher's site
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