UID:
almahu_9949285175802882
Format:
XVI, 180 p.
,
online resource.
Edition:
1st ed. 2001.
ISBN:
9783642576126
Series Statement:
Contributions to Economics,
Content:
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.
Note:
I. Introduction -- 1. Introduction -- 2. The Core Topics; Learning and Computational Economics -- 3. An Exemplary Introduction to Structure and Application of Genetic Algorithms in Economic Research -- II. General Analysis of Genetic Algorithms -- 4. Methods for the General Analysis of Genetic Algorithms as Economic Learning Techniques -- 5. Statistical Aspects of the Analysis of Economic Genetic Algorithms -- III. Economic Applications and Technical Variations -- 6. Modifications: Election and Meta¡ªLearning -- 7. Extensions: Variable Time Horizon of Selection -- 8. Algorithms with Real Valued Coding -- 9. A Multi Population Algorithm -- 10. Final Remarks.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783790813845
Additional Edition:
Printed edition: ISBN 9783642576133
Language:
English
DOI:
10.1007/978-3-642-57612-6
URL:
https://doi.org/10.1007/978-3-642-57612-6
