An Automated Learning Process in Market Engineering

F. Szidarovszky and H. Qiao (USA)


Oligopoly, market price, learning


The profits of industrial firms and service suppliers depend on the costs and on the market price. The companies are able to find estimates of the price function based on earlier data, however the lack of the knowledge of the production levels of the rivals makes their estimates uncertain. In this paper, a dynamic learning process that is based on the discrepancies between believed and actual market prices is introduced so the firms are able to adaptively adjust their price estimates. Conditions are given for the global asymptotical stability of the corresponding system to guarantee that the learning process converges to the full knowledge of the price function.

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