Toward an Agent-Based Computational Modeling of Bargaining Strategies in Double Auction Markets with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Chen:2000:TAB,
  author =       "Shu-Heng Chen",
  title =        "Toward an Agent-Based Computational Modeling of
                 Bargaining Strategies in Double Auction Markets with
                 Genetic Programming",
  booktitle =    "Intelligent Data Engineering and Automated Learning -
                 IDEAL 2000: Data Mining, Financial Engineering, and
                 Intelligent Agents",
  editor =       "Kwong Sak Leung and Lai-Wan Chan and Helen Meng",
  year =         "2000",
  series =       "Lecture Notes in Computer Science",
  volume =       "1983",
  pages =        "517--531",
  address =      "Shatin, N.T., Hong Kong, China",
  month =        "13-15 " # dec,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-41450-9",
  CODEN =        "LNCSD9",
  ISSN =         "0302-9743",
  bibdate =      "Tue Sep 10 19:08:58 MDT 2002",
  URL =          "http://www.aiecon.org/staff/shc/pdf/toward_an_agent.pdf",
  URL =          "http://citeseer.ist.psu.edu/463839.html",
  DOI =          "doi:10.1007/3-540-44491-2_76",
  acknowledgement = ack-nhfb,
  size =         "15 pages",
  abstract =     "Using genetic programming, this paper proposes an
                 agent- based computational modelling of double auction
                 (DA) markets in the sense that a DA market is modeled
                 as an evolving market of autonomous interacting traders
                 (automated software agents). The specific DA market on
                 which our modeling is based is the Santa Fe DA market
                 ([12], [13]), which in structure, is a discrete-time
                 version of the Arizona continuous- time experimental DA
                 market ([14], [15]).",
}

Genetic Programming entries for Shu-Heng Chen

Citations