Applying Multi-Objective Evolutionary Computing to Auction Mechanism Design

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@TechReport{oai:CiteSeerPSU:554389,
  title =        "Applying Multi-Objective Evolutionary Computing to
                 Auction Mechanism Design",
  author =       "Steve Phelps and Simon Parsons and Elizabeth Sklar and 
                 Peter McBurney",
  citeseer-isreferencedby = "oai:CiteSeerPSU:92933",
  citeseer-references = "oai:CiteSeerPSU:534053; oai:CiteSeerPSU:280312;
                 oai:CiteSeerPSU:255684; oai:CiteSeerPSU:345471;
                 \cite{oai:CiteSeerPSU:531021}; oai:CiteSeerPSU:342213",
  annote =       "The Pennsylvania State University CiteSeer Archives",
  language =     "en",
  oai =          "oai:CiteSeerPSU:554389",
  rights =       "unrestricted",
  institution =  "Department of Computer Science, University of
                 Liverpool",
  year =         "2002",
  number =       "ULCS-02-031",
  address =      "UK",
  keywords =     "genetic algorithms, genetic programming, auctions,
                 evolutionary computation, mechanism design,
                 multi-objective optimisation",
  URL =          "http://www.csc.liv.ac.uk/research/techreports/tr2002/ulcs-02-031.pdf",
  URL =          "http://citeseer.ist.psu.edu/554389.html",
  abstract =     "The mechanism design problem in economics is about
                 designing rules of interaction for market games which
                 aim to yield a globally desirable result in the face of
                 self-interested agents who may take advantage of the
                 mechanism in order to maximise their own individual
                 outcomes. This problem can be extremely complex.
                 Traditionally, economists have used game theory and
                 other formal methods to construct mechanism rules. In
                 this paper, we report on an alternative approach which
                 we hope will eventually yield more robust solutions
                 than the present analytical counterparts. Our
                 methodology views mechanism design as a multi-objective
                 optimisation problem and addresses the problem using
                 genetic programming. This paper reports on preliminary
                 work in this direction where we evolve an auction
                 pricing-rule for a continuous double auction using a
                 multi-objective fitness function.",
  size =         "6 pages",
}

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

Citations