Aksoy, Hakan2016-01-082016-01-081997http://hdl.handle.net/11693/17907Ankara : Institute of Economics and Social Sciences of Bilkent University, 1997.Thesis (Master's) -- Bilkent University, 1997.Includes bibliographical references leaves 35-37There 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.v, 37 leaves, xlv, [124] pages of platesEnglishinfo:eu-repo/semantics/openAccessDynamic GamesBounded RationalityClassifier SystemsTwo Armed Bandit ProblemKiyotaki and Wright Model of MoneyLearningExperimentationImitationLB1029.G3 A37 1997Educational games.Differential games.Dynamic programming.Game theory.Noncooperative games.A model of boundedly rational learning in dynamic gamesThesis