Internet auctions with artificial adaptive agents: A study on market design
AbstractWe develop a model of internet auctions with the aim of understanding how rules for ending such auctions (a "hard"- or "soft"-close) affect bidding behavior. We model bidding strategies using finite automata and report results from simulations involving populations of artificial bidders who update their strategies using a genetic algorithm. Our model is shown to deliver late or early bidding behavior, depending on whether the auction has a hard- or soft-close rule in accordance with the empirical evidence. We report on other interesting properties of our model and offer some conclusions from a market design point of view.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Behavior & Organization.
Volume (Year): 67 (2008)
Issue (Month): 2 (August)
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Web page: http://www.elsevier.com/locate/jebo
Other versions of this item:
- M.Utku Unver & John Dufffy, 2005. "Internet Auctions with Artificial Adaptive Agents: A Study on Market Design," Working Papers 260, University of Pittsburgh, Department of Economics, revised Jan 2005.
- John Duffy & M. Utku Unver, 2005. "Internet Auctions with Artificial Adaptive Agents: A Study on Market Design," Computational Economics 0510001, EconWPA, revised 07 Oct 2005.
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
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