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Incomplete Information: Structure, Inference, Complexity

  • Stéphane P. Demri
  • Ewa S. Orłowska

Table of contents

  1. Front Matter
    Pages I-XVIII
  2. Mathematical Prerequisites

    1. Stéphane P. Demri, Ewa S. Orłowska
      Pages 1-12
  3. Structures with Incomplete Information

    1. Front Matter
      Pages 13-13
    2. Stéphane P. Demri, Ewa S. Orłowska
      Pages 15-36
    3. Stéphane P. Demri, Ewa S. Orłowska
      Pages 37-69
    4. Stéphane P. Demri, Ewa S. Orłowska
      Pages 71-90
  4. Introduction to Information Logics

    1. Front Matter
      Pages 91-91
    2. Stéphane P. Demri, Ewa S. Orłowska
      Pages 93-116
    3. Stéphane P. Demri, Ewa S. Orłowska
      Pages 117-136
  5. Proof Systems for Information Logics

    1. Front Matter
      Pages 137-137
    2. Stéphane P. Demri, Ewa S. Orłowska
      Pages 139-170
    3. Stéphane P. Demri, Ewa S. Orłowska
      Pages 171-192
    4. Stéphane P. Demri, Ewa S. Orłowska
      Pages 193-216
  6. Computational Aspects of Information Logics

    1. Front Matter
      Pages 217-217
    2. Stéphane P. Demri, Ewa S. Orłowska
      Pages 219-241
    3. Stéphane P. Demri, Ewa S. Orłowska
      Pages 243-266
    4. Stéphane P. Demri, Ewa S. Orłowska
      Pages 267-293
  7. Representability and Duality

    1. Front Matter
      Pages 295-295
    2. Stéphane P. Demri, Ewa S. Orłowska
      Pages 297-320
    3. Stéphane P. Demri, Ewa S. Orłowska
      Pages 321-354
    4. Stéphane P. Demri, Ewa S. Orłowska
      Pages 355-377
  8. Back Matter
    Pages 379-408

About this book

Introduction

The construction of any broadly understood theory of information or infor­ mation processing system involves two major methodological processes: (1) abstraction and analysis, (2) reasoning and computing. This monograph is a realisation of these two processes in relation to the study of incompleteness of information. The paradigm we are working with is inspired by a rough-set approach to data analysis: the formalisms we develop enable the use of a non­ invasive data representation. This means that the only information which is and must be used in the process of analysis is the actual information that is to be analysed; we do not require any additional sources of information. An abstraction is formed in the process of conception, design, and develop­ ment of structures. Then analysis leads to a selection of a class of structures. In this book we delineate a class of informational structures that enable us to represent both numerical and non-numerical information and we analyse var­ ious manifestations of its incompleteness. We discuss several general types of incompleteness of information which are grounded in a rough-set-style view of imprecision and uncertainty. Manifestations of these types of incompleteness in information systems are investigated.

Keywords

complexity data analysis deduction incomplete information information system knowledge rough set

Authors and affiliations

  • Stéphane P. Demri
    • 1
    • 2
  • Ewa S. Orłowska
    • 3
  1. 1.Laboratoire Spécification et VérificationCNRS UMR 8643, ENS de CachanCachan CedexFrance
  2. 2.Laboratoire LeibnizGrenobleFrance
  3. 3.National Institute of TelecommunicationsWarszawaPoland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-04997-6
  • Copyright Information Springer-Verlag Berlin Heidelberg 2002
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-07540-7
  • Online ISBN 978-3-662-04997-6
  • Series Print ISSN 1431-2654
  • Buy this book on publisher's site