Using genetic programming to optimise pricing rules for a double auction market

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

@InProceedings{Phelps:2003:AEC,
  title =        "Using genetic programming to optimise pricing rules
                 for a double auction market",
  author =       "Steve Phelps and Peter Mcburney and 
                 Elizabeth Sklar and Simon Parsons",
  year =         "2003",
  keywords =     "genetic algorithms, genetic programming",
  annote =       "The Pennsylvania State University CiteSeerX Archives",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  description =  "genetic programming to optimise pricing rules for a",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.526.6836",
  rights =       "Metadata may be used without restrictions as long as
                 the oai identifier remains attached to it.",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.526.6836",
  URL =          "http://spider.sci.brooklyn.cuny.edu/~parsons/projects/mech-design/publications/aec03.pdf",
  size =         "8 pages",
  abstract =     "The mechanism design problem in economics is about
                 designing rules of interaction for market games so they
                 yield a globally desirable result in the face of
                 self-interested agents. This problem, which is of
                 importance for ecommerce since much E-commerce is
                 carried out through auctions, can be extremely complex.
                 Traditionally, economists have tried using game theory
                 and other formal methods to construct suitable
                 mechanism rules. However, analytical methods typically
                 oversimplify the problem and so the resulting rules are
                 not necessarily robust. In this paper, we report on an
                 alternative approach which we hope will eventually
                 yield more robust solutions. Our methodology views
                 mechanism design as a multi-objective optimisation
                 problem and addresses the problem using genetic
                 programming.",
  notes =        "Proceedings of the workshop on Agents for Electronic
                 Commerce, Pittsburgh, PA,, USA, 2003.",
}

Genetic Programming entries for Steve Phelps Peter McBurney Elizabeth Sklar Simon Parsons

Citations