Applications of Learning Classifier Systems for Simulating Learning Organizations

FBS 10 (Series 'Fortschrittsberichte Simulation / Advances in Simulation'); Digital Reprint ISBN: 978-3-903347-10-6, DOI: 10.11128/fbs.10, ARGESIM Wien 2020

About this Book

In this volume the necessity and the practicality of the employment of complex adaptive systems for describing recent economic happenings is discussed. They are compared with common analytical modelling techniques to give an idea about  the advantages and shortcomings of both approaches. Then some methods that are qualified to implement complex adaptive systems are being explained. Special emphasis is dedicated to learning classifier systems and genetic algorithms. In the following some examples are provided to illustrate possibilities and also restrictions of the usage of such procedures. Based on this elaborations two comprehensive economic models are formulated and analysed. The interpretation of the simulation results delivers valuable hints for determining successful business strategies.

About the Author

Thomas Fent studied Applied Mathematics at the Vienn University of Technology. During his diploma study he was involved in several research projects at the Institute of Econometrics, Operations Research and Systems Theory at the Vienna University of Technology. There he worked essentiallyin the field of intertemporal optimisation. After graduating diploma study he worked for four years at the Center for Business Sudies at the University of Vienna. At this institution he was busy in science and teaching. Among others he participated in the integrated research program "Adaptive Information Systems and Modellingin Economics and Management Science". A part of his results gained in this program is collected in this volume. Currently Thomas Fent is employed at the Austrian Academy of Sciences at the Institute for Demography.