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Using Genetics Based Machine Learning to find Strategies for Product Placement in a dynamic Market

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  • Fent, Thomas

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.

Suggested Citation

  • Fent, Thomas, 1999. "Using Genetics Based Machine Learning to find Strategies for Product Placement in a dynamic Market," MPRA Paper 2837, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:2837
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    File URL: https://mpra.ub.uni-muenchen.de/2837/1/MPRA_paper_2837.pdf
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    References listed on IDEAS

    as
    1. Thomas Brenner, 1998. "Can evolutionary algorithms describe learning processes?," Journal of Evolutionary Economics, Springer, vol. 8(3), pages 271-283.
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    More about this item

    Keywords

    product positioning; market simulation; heterogeneous agents; learning classifier systems; genetic algorithms; adaptive systems modelling;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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