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This book deals with the learning behavior of boundedly rational agents in economic systems. In particular, the modeling of learning populations by genetic algorithms is studied in detail. After an extensive review and discussion of the existing literature in the first part, a mathematical analysis of the dynamic properties of genetic algorithm learning in the general framework of systems with a state dependent fitness function is provided. It is shown that co-evolutionary economic models typically fall into this class and the usefulness of the analytical results derived is illustrated in several game theoretic and microeconomic models. The mathematical analysis is complemented by extensive simulation analyses. The last part of the book demonstrates how the obtained theory may be used to design the algorithm such that the learning of equilibria of the economic system is facilitated.
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Previews available in: English
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1
Adaptive Learning by Genetic Algorithms: Analytical Results and Applications to Economical Models
2012, Springer
in English
3662002116 9783662002117
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2
Adaptive Learning by Genetic Algorithms: Analytical Results and Applications to Economic Models
1999, Springer Berlin Heidelberg
electronic resource :
in English
- Second, rev. and enlarged edition.
3642621066 9783642621062
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Berlin, Heidelberg
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- Created June 28, 2019
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