• DocumentCode
    3414005
  • Title

    Evolved hybrid auction mechanisms in non-ZIP trader marketplaces

  • Author

    Cliff, Dave ; Walia, Vibhu ; Byde, Andrew

  • Author_Institution
    Hewlett-Packard Labs., UK
  • fYear
    2003
  • fDate
    20-23 March 2003
  • Firstpage
    167
  • Lastpage
    174
  • Abstract
    A previous paper by D. Cliff (see ibid., 2002) demonstrated that a genetic algorithm could be used to automatically discover new optimal auction mechanisms for automated electronic marketplaces populated by software-agent traders. Significantly, the new auction mechanisms are often unlike traditional mechanisms designed by humans for human traders; rather, they are peculiar hybrid mixtures of established styles of mechanism. This previous work used software agents running the ZIP trader algorithm (recently shown to outperform human traders). We provide the first demonstration that qualitatively similar results (i.e., non-standard hybrid mechanism designs being optimal) are also given when similar experiments are performed using a different trader algorithm, namely Gode & Sunder´s (1993) ZI-C traders. Thus, the paper is the first to offer significant evidence that evolved hybrid auction mechanisms may be found that out-perform traditional market mechanisms for many styles of trader-agent.
  • Keywords
    commerce; electronic trading; genetic algorithms; software agents; ZI-C traders; ZIP trader algorithm; auction markets; automated electronic marketplaces; evolutionary optimization; evolved hybrid auction mechanisms; genetic algorithm; human traders; nonZIP trader marketplaces; nonstandard hybrid mechanism designs; optimal auction mechanisms; peculiar hybrid mixtures; software agents; software-agent traders; trader algorithm; trader-agent; Computer science; Consumer electronics; Environmental economics; Genetic algorithms; Humans; Laboratories; Machine learning; Robustness; Software agents; Software algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Financial Engineering, 2003. Proceedings. 2003 IEEE International Conference on
  • Print_ISBN
    0-7803-7654-4
  • Type

    conf

  • DOI
    10.1109/CIFER.2003.1196257
  • Filename
    1196257