Using co-evolutionary programming to simulate strategic behaviour in markets

被引:0
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作者
Tony Curzon Price
机构
[1] Energy Policy Group,
[2] Imperial College,undefined
[3] 48 Princes Gardens,undefined
[4] London SW7 2PE,undefined
[5] UK (e-mail: j.curzon-price@ic.ac.uk),undefined
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关键词
Key words: Industrial organisation; Evolutionary programming; Genetic algorithms; Strategy selection; Learning; JEL-classification: C61; C72; D43; D44; L13; L94;
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摘要
This paper describes the use of a genetic algorithm (GA) to model several standard industrial organisation games: Bertrand and Cournot competition, a vertical chain of monopolies, and a simple model of an electricity pool. The intention is to demonstrate that the GA performs well as a modelling tool in these standard settings, and that evolutionary programming therefore has a potential role in applied work requiring detailed market simulation. The advantages of using a GA over scenario analysis for applied market simulation are outlined. Also explored are the way in which the equilibria discovered by the GA can be interpreted, and what the market analogue for the GA process might be.
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页码:219 / 254
页数:35
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