Modeling Implicit Collusion Using Coevolution
成果类型：
Article
署名作者：
Anderson, E. J.; Cau, T. D. H.
署名单位：
University of Sydney; University of New South Wales Sydney
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.1080.0631
发表日期：
2009
页码：
439-455
关键词：
摘要：
Many oligopolies operate as a repeated game. In such circumstances, it can be expected that profit-maximising participants may engage in implicit collusion to profitably increase spot market prices. This paper models the emergence of such implicit collusion in a stylised market model using a coevolutionary approach. Players bid supply functions made up of a finite number of linear pieces. Each player uses a genetic algorithm to find state-based strategies depending on the price and demand in the last period and the predicted demand in the next period. We consider a symmetric duopoly and demonstrate that collusive behaviour can be learned even when there is very limited information available to the participants. Moreover, we show a type of implicit collusive behaviour that occurs even though the system does not settle into a stable equilibrium. We use a wholesale electricity market, in which supply function bids are typical, as a motivating example throughout this paper.