Adaptive Learning by Genetic Algorithms: Analytical Results and Applications to Economic Models / Edition 2by Herbert Dawid
Pub. Date: 05/28/1999
Publisher: Springer Berlin Heidelberg
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
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.
- Springer Berlin Heidelberg
- Publication date:
- Edition description:
- 2nd, rev. a. enlarged ed. 1999
- Product dimensions:
- 6.10(w) x 9.25(h) x 0.02(d)
Table of Contents
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.
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