Using genetics based machine learning to find strategies for product placement in a dynamic market

Fent, Thomas (1999) Using genetics based machine learning to find strategies for product placement in a dynamic market. Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science", 55. SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, Vienna.

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Abstract

In this paper we discuss the necessity of models including complex adaptive systems in order to eliminate the shortcomings of neoclassical models based on equilibrium theory. A simulation model containing artificial adaptive agents is used to explore the dynamics of a market of highly replaceable products. A population consisting of two classes of agents is implemented to observe if methods provided by modern computational intelligence can help finding a meaningful strategy for product placement. During several simulation runs it turned out that the agents using CI-methods outperformed their competitors. (author's abstract)

Item Type: Paper
Keywords: Produktpositionierung / Adaptives System
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Departments > Marketing > Service Marketing und Tourismus
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Depositing User: Repository Administrator
Date Deposited: 06 Mar 2002 13:55
Last Modified: 22 Oct 2019 00:41
URI: https://epub.wu.ac.at/id/eprint/694

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