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Learning in Economics

Analysis and Application of Genetic Algorithms

  • Thomas Riechmann

Part of the Contributions to Economics book series (CE)

Table of contents

  1. Front Matter
    Pages I-XV
  2. Introduction

  3. General Analysis of Genetic Algorithms

  4. Economic Applications and Technical Variations

    1. Front Matter
      Pages 71-71
    2. Thomas Riechmann
      Pages 73-96
    3. Thomas Riechmann
      Pages 97-113
    4. Thomas Riechmann
      Pages 115-136
    5. Thomas Riechmann
      Pages 137-166
    6. Thomas Riechmann
      Pages 167-168
  5. Back Matter
    Pages 169-179

About this book

Introduction

The book is dedicated to the use of genetic algorithms in theoretical economic research. Genetic algorithms offer the chance of overcoming the limitations traditional mathematical tractability puts on economic research and thus open new horzions for economic theory. The book reveals close relationships between the theory of economic learning via genetic algorithms, dynamic game theory, and evolutionary economics.
Genetic algorithms are here introduced as metaphors for processes of social and individual learning in economics. The book gives a simple description of the basic structures of economic genetic algorithms, followed by an in-depth analysis of their working principles. Several well-known economic models are reconstructed to incorporate genetic algorithms. Genetic algorithms thus help to find genuinely new results of well-known economic problems.

Keywords

Economic Genetic Algorithms Economic Modeling Economic Theory Genetic Algorithms Genetische Algorithmen Learning in Economics Lernen in der Ökonomie Theory of Economic Learning Wirtschaftstheorie calculus game theory linear optimization ökonomische Modelle

Authors and affiliations

  • Thomas Riechmann
    • 1
  1. 1.Department for EconomicsUniversity of HannoverHannoverGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-57612-6
  • Copyright Information Physica-Verlag Heidelberg 2001
  • Publisher Name Physica, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-7908-1384-5
  • Online ISBN 978-3-642-57612-6
  • Series Print ISSN 1431-1933
  • Buy this book on publisher's site
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