Internet auctions with artificial adaptive agents: A study on market design

John Duffy () and M. Utku Ünver

Journal of Economic Behavior & Organization, 2008, vol. 67, issue 2, pages 394-417

Abstract: We 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.

Date: 2008
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Related works:
Working Paper: Internet Auctions with Artificial Adaptive Agents: A Study on Market Design (2005)
Working Paper: Internet Auctions with Artificial Adaptive Agents: A Study on Market Design (2005)
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Persistent link: http://EconPapers.repec.org/RePEc:eee:jeborg:v:67:y:2008:i:2:p:394-417

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