Adaptive Learning by Genetic Algorithms (Hardcover)

Herbert Dawid

ISBN 10: 3540656073 / ISBN 13: 9783540656074

Editore: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 1999

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Hardcover. 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. I have also added a new section in chapter 3 which deals with the question how well empirically observed phenomena can be explained by GA simulations. A new section in chapter 6 presents a rather extensive analysis of the behavior of a two population GA in the framework of a sealed bid double auction market. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Codice articolo 9783540656074

Dati bibliografici

• Titolo: Adaptive Learning by Genetic Algorithms (Hardcover)
• Editore: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin
• Data di pubblicazione: 1999
• Lingua: Inglese
• ISBN 10: 3540656073
• ISBN 13: 9783540656074
• Rilegatura: Hardcover
• Edizione: seconda edizione
• Condizione: new

Descrizione articolo

Riassunto

The fact that I have the opportunity to present a second edition of this monograph is an indicator for the growing size of the community concerned with agent-based computational economics. The rapid developments in this field make it very difficult to keep a volume like this, which is partly devoted to surveying the literature, up to date. I have done my best to incorporate the relevant new developments in this revised edition but it is in the nature of such a work that the selection of material covered is biased by the authors personal interest and his informational constraints. My apologies go to all researchers in this field whose work is not or not adequately represented in this book. Besides the correction of some errors and typos several additions have been made. In the literature survey sections 2.4 (which was also reorganized) and 3.5 new material was added. I have also added a new section in chapter 3 which deals with the question how well empirically observed phenomena can be explained by GA simulations. A new section in chapter 6 presents a rather extensive analysis of the behavior of a two population GA in the framework of a sealed bid double auction market. Further minor additions and changes were made throughout the text.

Contenuti

Introduction.- Bounded Rationality and Artificial Intelligence.- Bounded Rationality in Economics.- Artificially Intelligent Agents in Economic Systems.- Learning Techniques of Artificially Intelligent Agents.- Some Applications of CI Methods in Economic Systems.- Potentiality and Problems of CI Techniques in Economics.- Genetic Algorithms.- What are Genetic Algorithms?.- The Structure of Genetic Algorithms.- Genetic Operators.- Genetic Algorithms with a Non-Standard Structure.- Some Analytical Approaches to Model Genetic Algorithms.- Do Genetic Algorithms Describe Adaptive Learning?.- Genetic Algorithms with a State Dependent Fitness Function.- State Dependency in Economic Systems.- A Markov Model for Systems with a State Dependent Fitness Function.- The Difference Equations Describing the GA.- Deviation from the Markov Process.- A Numerical Example.- Stability of the Uniform States.- Two-Population Models.- Genetic Learning in Evolutionary Games.- Equilibria and Evolutionary Stability.- Learning in Evolutionary Games.- Learning by a Simple Genetic Algorithm.- Two-Population Contests.- Simulations with Genetic Algorithms in Economic Systems.- A Model of a Competitive Market.- An Overlapping Generations Model with Fiat Money.- A Sealed Bid Double Auction Market.- Stability and Encoding.- The Cobweb Example Revisited.- Impact of a Change in Encoding and Scaling.- A Method for Finding Economic Equilibria.- Conclusions.- Basic Definitions and Results Used.- Time Homogeneous Markov Chains.- Nonlinear Difference Equations and Stability.- Calculation of the Equilibria of the Evolutionary Games in Chapter 5.- Rock-Scissor-Paper Games.- The GA Deceptive Game GAD.- The Games G1 and G2.- Proof of Proposition 6.3.1.