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Predictor Agent for Online Auctions

  • Deborah Lim
  • Patricia Anthony
  • Chong Mun Ho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4953)

Abstract

In the last few years online auctions have become a popular method in purchasing and selling goods over the Internet. Bidding in an online auction is a challenging task since we do not know the outcome of our bid until the auction is closed. It is difficult to predict the winning bid of any particular auction. Hence, many investors have been trying to find a better way to predict auction closing price accurately. Knowing the closing price of a given auction would be an advantage since this information will be useful and can be used to ensure a win in a given auction. This information is beneficial to bidders since the outcome of the auction is dependent on several factors such as the number of auctions selling the same item, the number of bidders participating in that auction as well as the behaviour of every individual bidder. If the closing price of an auction is known, then bidder could decide which auction to participate and at what price. This paper reports on the development of a predictor agent that attempts to predict the online auction closing price. The performance of this predictor agent is compared with two well known techniques which are the Simple Exponential Function and the Time Series in a simulated auction environment.

Keywords

Agent Grey Theory Time Series Simple Exponential Function 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Deborah Lim
    • 1
  • Patricia Anthony
    • 1
  • Chong Mun Ho
    • 1
  1. 1.School of Engineering and Information TechnologyUniversiti Malaysia SabahKota KinabaluMalaysia

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