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