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" Adaptive Learning by Genetic Algorithms "
by Herbert Dawid.
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BL
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| Record Number
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578070
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b407289
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| Main Entry
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Dawid, Herbert.
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| Title & Author
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Adaptive Learning by Genetic Algorithms : Analytical Results and Applications to Economic Models /\ by Herbert Dawid.
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| Edition Statement
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Second, Revised and Enlarged Edition.
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| Publication Statement
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Berlin, Heidelberg :: Springer Berlin Heidelberg :: Imprint: Springer,, 1999.
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| ISBN
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9783642181429
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: 9783642621062
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| Contents
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Introduction -- Bounded Rationality and Artificial Intelligence -- Genetic Algorithms -- Genetic Algorithms with a State Dependent Fitness Function -- Genetic Learning in Evolutionary Games -- Simulations with Genetic Algorithms in Economic Systems -- Stability and Encoding -- Conclusions -- Basic Definitions and Results Used -- Calculation of the Equilibria of the Evolutionary Games in Chapter 5 -- Proof of Proposition 6.3.1. The complete table of contents can be found on the Internet: http://www.springer.de.
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| Abstract
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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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Economics.
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Economics, Mathematical.
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SpringerLink (Online service)
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