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Connectionist Approaches in Economics and Management Sciences

  • Cédric Lesage
  • Marie Cottrell

Part of the Advances in Computational Management Science book series (AICM, volume 6)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Advances in Connectionist Approaches in Economics and Management Sciences

    1. Front Matter
      Pages 1-1
    2. Didier Dubois, Eyke Hüllermeier, Henri Prade
      Pages 31-48
    3. Bernard Paulre
      Pages 71-108
  3. Applications in Economics and Management Sciences

    1. Front Matter
      Pages 109-109
    2. Séverine Lemiere, Corinne Perraudin, Héloïse Petit
      Pages 131-144
    3. Jacques-Marie Aurifeille, Stéphane Manin
      Pages 145-163
    4. Amaury Lendasse, John. Lee, Eric De Bodt, Vincent Wertz, Michel Verleysen
      Pages 203-214
    5. Bertrand Maillet, Patrick Rousset
      Pages 233-259

About this book

Introduction

Since the beginning of the 1980's, a lot of news approaches of biomimetic inspiration have been defined and developed for imitating the brain behavior, for modeling non linear phenomenon, for providing new hardware architectures, for solving hard problems. They are named Neural Networks, Multilayer Perceptrons, Genetic algorithms, Cellular Automates, Self-Organizing maps, Fuzzy Logic, etc. They can be summarized by the word of Connectionism, and consist of an interdisciplinary domain between neuroscience, cognitive science and engineering. First they were applied in computer sciences, engineering, biological models, pattern recognition, motor control, learning algorithms, etc. But rapidly, it appeared that these methods could be of great interest in the fields of Economics and Management Sciences. The main difficulty was the distance between researchers, the difference in the vocabulary used by the ones and the others, their basic background. The main notions used by these new techniques were not familiar to the Social and Human Sciences researchers. What are they ? Four of them are now very briefly introduced, but the reader will find more information in the following chapters.

Keywords

Hidden Markov Model Lemma algorithms evolution fuzzy modeling

Editors and affiliations

  • Cédric Lesage
    • 1
  • Marie Cottrell
    • 2
  1. 1.CREREG CNRSUniversity of RennesFrance
  2. 2.SAMOS MATISSE CNRSUniversity of Paris 1France

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4757-3722-6
  • Copyright Information Springer-Verlag US 2003
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4419-5379-7
  • Online ISBN 978-1-4757-3722-6
  • Series Print ISSN 1388-4301
  • Buy this book on publisher's site