Learning In Economics: Analysis And Application Of Genetic Algorithms by Thomas RiechmannLearning In Economics: Analysis And Application Of Genetic Algorithms by Thomas Riechmann

Learning In Economics: Analysis And Application Of Genetic Algorithms

byThomas Riechmann

Paperback | March 13, 2001

Pricing and Purchase Info

$136.79 online 
$164.50 list price save 16%
Earn 684 plum® points

Prices and offers may vary in store


In stock online

Ships free on orders over $25

Not available in stores


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.
Title:Learning In Economics: Analysis And Application Of Genetic AlgorithmsFormat:PaperbackDimensions:180 pagesPublished:March 13, 2001Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3790813842

ISBN - 13:9783790813845


Table of Contents

Introduction: Learning and Computational Economics.- An Exemplary Introduction to Structure and Application of Genetic Algorithms in Economic Research. General Analysis of Genetic Algorithms: Methods for the General Analysis of Genetic Algorithms as Economic Learning Techniques. Economic Applications and Technical Variations: Modifications: Election and Meta-Learning.- Extensions: Variable Time Horizon of Selection.- Algorithms with Real Valued Coding.- A Multi Population Algorithm.- Final Remarks.