Seller's Strategies for Predicting Winning Bid Prices in Online Auctions

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@InProceedings{Kovalchuk:2008:CIMCA,
  author =       "Yevgeniya Kovalchuk",
  title =        "Seller's Strategies for Predicting Winning Bid Prices
                 in Online Auctions",
  booktitle =    "International Conference on Computational Intelligence
                 for Modelling Control Automation",
  year =         "2008",
  month =        dec,
  pages =        "1--6",
  keywords =     "genetic algorithms, genetic programming, first price
                 sealed bid reverse auctions, genetic programming
                 learning techniques, neural networks, online auctions,
                 seller strategies, trading agent competition supply
                 chain management game, winning bid price prediction,
                 electronic commerce, learning (artificial
                 intelligence), neural nets, pricing, supply chain
                 management",
  DOI =          "doi:10.1109/CIMCA.2008.60",
  abstract =     "Online auctions have become extremely popular in
                 recent years. Ability to predict winning bid prices
                 accurately can help bidders to maximize their profit.
                 This paper proposes a number of strategies and
                 algorithms for performing such predictions for the
                 first price sealed bid reverse auctions (FPSBRA). The
                 neural networks (NN) and genetic programming (GP)
                 learning techniques are used in the models. The
                 algorithms are tested in the trading agent competition
                 supply chain management (TAC SCM) game, where
                 manufacture agents compete for customers' orders
                 following the rules of the FPSBRA. Although all the
                 proposed algorithms demonstrate the potential for
                 predicting winning bid prices in competitive and
                 dynamic environments, some of them perform more
                 accurately than the others.",
  notes =        "Also known as \cite{5172590}",
}

Genetic Programming entries for Yevgeniya Kovalchuk

Citations