Biology & Life Sciences, Robotics & Artificial Intelligence, Artificial Intelligence (AI), Mathematics, Robotics & Artificial Intelligence, Genetics, Mathematical Modeling, Economics - Mathematical & Quanitative Methods
Adaptive Learning by Genetic Algorithms: Analytical Results and Applications to Economic Models
Herbert Dawid
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Overview
This book deals with the learning behavior of bounded 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 coevolutionary 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.Book Details
Published
December 31, 2012
Publisher
Springer-Verlag New York, LLC
Pages
213
Format
Hardcover
ISBN
9783642621062