Information Algebras

Generic Structures For Inference

  • Jürg Kohlas

Part of the Discrete Mathematics and Theoretical Computer Science book series (DISCMATH)

Table of contents

  1. Front Matter
    Pages i-x
  2. Jürg Kohlas
    Pages 1-6
  3. Jürg Kohlas
    Pages 7-40
  4. Jürg Kohlas
    Pages 41-94
  5. Jürg Kohlas
    Pages 95-129
  6. Jürg Kohlas
    Pages 131-158
  7. Jürg Kohlas
    Pages 159-207
  8. Jürg Kohlas
    Pages 209-250
  9. Back Matter
    Pages 251-266

About this book


Information usually comes in pieces, from different sources. It refers to different, but related questions. Therefore information needs to be aggregated and focused onto the relevant questions. Considering combination and focusing of information as the relevant operations leads to a generic algebraic structure for information. This book introduces and studies information from this algebraic point of view. Algebras of information provide the necessary abstract framework for generic inference procedures. They allow the application of these procedures to a large variety of different formalisms for representing information. At the same time they permit a generic study of conditional independence, a property considered as fundamental for knowledge presentation. Information algebras provide a natural framework to define and study uncertain information. Uncertain information is represented by random variables that naturally form information algebras. This theory also relates to probabilistic assumption-based reasoning in information systems and is the basis for the belief functions in the Dempster-Shafer theory of evidence.


AI Applied Mathematics Computer Science Economics Engineering Management Science Random variable Statistics algebra algorithms information system

Authors and affiliations

  • Jürg Kohlas
    • 1
  1. 1.Department of InformaticsUniversity of FribourgFribourgSwitzerland

Bibliographic information