A model of boundedly rational learning in dynamic games

Date
1997
Instructor
Source Title
Print ISSN
Electronic ISSN
Publisher
Bilkent University
Volume
Issue
Pages
Language
English
Type
Thesis
Journal Title
Journal ISSN
Volume Title
Abstract

There are various computer-based algorithms about boundedly rational players’ learning how to behave in dynamic games, including classifier systems, genetic algorithms and neural networks. Some examples of studies using boundedly rational players are Axelrod (1987), Miller (1989), Andreoni and Miller (1990) who use genetic algorithm and Marimon etal. (1990) and Arthur (1990) who use classifier systems. In this dissertation, a Two Armed Bandit Problem and the KiyotakiWright (1989) Economic Environment are constructed and the learning behaviour ol the boundedly rational players is observed by using classifier systems in computer programs. From the simulation results, we observe that experimentation and imitation enables faster convergence to the correct decision rules of players in both repeated static decision problems and dynamic games.

Course
Other identifiers
Book Title
Keywords
Dynamic Games, Bounded Rationality, Classifier Systems, Two Armed Bandit Problem, Kiyotaki and Wright Model of Money, Learning, Experimentation, Imitation
Citation
Published Version (Please cite this version)