Modeling intelligence of learning agents in an artificial double auction market

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@InProceedings{Chen:2009:CIFEr,

• author = "Shu-Heng Chen and Chung-Ching Tai",
• title = "Modeling intelligence of learning agents in an artificial double auction market",
• booktitle = "IEEE Symposium on Computational Intelligence for Financial Engineering, CIFEr '09",
• year = "2009",
• month = "30 " # mar # "-" # apr # " 2",
• pages = "36--42",
• keywords = "genetic algorithms, genetic programming, artificial double auction market, individual intelligence modeling, learning agents, psychological, socioeconomic, software agents, commerce, psychology, socio-economic effects, software agents",
• DOI = "doi:10.1109/CIFER.2009.4937500",
• abstract = "In psychological as well as socioeconomic studies, individual intelligence has been found decisive in many domains. In this paper, we employ genetic programming as the algorithm of our learning agents who compete with other designed strategies extracted from the literature.We then discuss the possibility of using population size as a proxy parameter of individual intelligence of software agents. By modeling individual intelligence in this way, we demonstrate not only a nearly positive relation between individual intelligence and performance, but more interestingly the effect of decreasing marginal contribution of IQ to performance found in psychological literature.",
• notes = "Also known as \cite{4937500}",

}

Genetic Programming entries for Shu-Heng Chen Chung-Ching Tai

Citations