Fent, Thomas (1999): Using Genetics Based Machine Learning to find Strategies for Product Placement in a dynamic Market.
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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.
|Item Type:||MPRA Paper|
|Institution:||Vienna University of Economics and Business Administration|
|Original Title:||Using Genetics Based Machine Learning to find Strategies for Product Placement in a dynamic Market|
|Keywords:||product positioning; market simulation; heterogeneous agents; learning classifier systems; genetic algorithms; adaptive systems modelling|
|Subjects:||C - Mathematical and Quantitative Methods > C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C63 - Computational Techniques; Simulation Modeling
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C61 - Optimization Techniques; Programming Models; Dynamic Analysis
D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D83 - Search; Learning; Information and Knowledge; Communication; Belief
D - Microeconomics > D4 - Market Structure and Pricing > D40 - General
M - Business Administration and Business Economics; Marketing; Accounting > M3 - Marketing and Advertising > M31 - Marketing
C - Mathematical and Quantitative Methods > C7 - Game Theory and Bargaining Theory > C73 - Stochastic and Dynamic Games; Evolutionary Games; Repeated Games
|Depositing User:||Thomas Fent|
|Date Deposited:||20. Apr 2007|
|Last Modified:||21. Feb 2013 18:47|
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