Resource title

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

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Resource description

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) ; Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

Resource author

Thomas Fent

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Resource language

en

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application/pdf

Resource resource URL

http://epub.wu.ac.at/694/1/document.pdf

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