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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.

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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.

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