Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis

  • Uffe B. Kjærulff
  • Anders L. Madsen

Part of the Information Science and Statistics book series (ISS, volume 22)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Fundamentals

    1. Front Matter
      Pages 1-1
    2. Uffe B. Kjærulff, Anders L. Madsen
      Pages 3-15
    3. Uffe B. Kjærulff, Anders L. Madsen
      Pages 17-37
    4. Uffe B. Kjærulff, Anders L. Madsen
      Pages 39-67
    5. Uffe B. Kjærulff, Anders L. Madsen
      Pages 69-109
    6. Uffe B. Kjærulff, Anders L. Madsen
      Pages 111-142
  3. Model Construction

    1. Front Matter
      Pages 143-143
    2. Uffe B. Kjærulff, Anders L. Madsen
      Pages 145-189
    3. Uffe B. Kjærulff, Anders L. Madsen
      Pages 191-236
    4. Uffe B. Kjærulff, Anders L. Madsen
      Pages 237-288
  4. Model Analysis

    1. Front Matter
      Pages 289-289
    2. Uffe B. Kjærulff, Anders L. Madsen
      Pages 291-301
    3. Uffe B. Kjærulff, Anders L. Madsen
      Pages 303-325
    4. Uffe B. Kjærulff, Anders L. Madsen
      Pages 327-339
  5. Back Matter
    Pages 341-382

About this book

Introduction

Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new sections, in addition to fully-updated examples, tables, figures, and a revised appendix.  Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented on model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined based on numerous courses the authors have held for practitioners worldwide.  

Uffe B. Kjærulff holds a PhD on probabilistic networks and is an Associate Professor of Computer Science at Aalborg University. Anders L. Madsen of HUGIN EXPERT A/S holds a PhD on probabilistic networks and is an Adjunct Professor of Computer Science at Aalborg University.

Keywords

Bayesian Networks Graphical Models Influence Diagrams Model Analysis Model Construction Probabilistic Networks

Authors and affiliations

  • Uffe B. Kjærulff
    • 1
  • Anders L. Madsen
    • 2
  1. 1.Dept. Computer ScienceAalborg UniversityAalborgDenmark
  2. 2.Hugin Expert A/SAalborgDenmark

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-5104-4
  • Copyright Information Springer Science+Business Media New York 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Computer Science
  • Print ISBN 978-1-4614-5103-7
  • Online ISBN 978-1-4614-5104-4
  • Series Print ISSN 1613-9011
  • About this book