AN ADAPTIVE SHILL BIDDING AGENT

Jarrod Trevathan, Alan McCabe, Wayne Read

Abstract

This paper presents a software bidding agent that inserts fake bids on the seller’s behalf to inflate an auction’s price. This behaviour is referred to as shill bidding. Shill bidding is strictly prohibited by online auctioneers, as it defrauds unsuspecting buyers by forcing them to pay more for the item. The malicious bidding agent was constructed to aid in developing shill detection techniques. We have previously documented a simple shill bidding agent that incrementally increases the auction price until it reaches the desired profit target, or it becomes too risky to continue bidding. This paper presents an adaptive shill bidding agent which when used over a series of auctions with substitutable items, can revise its strategy based on bidding behaviour in past auctions. The adaptive agent applies a novel prediction technique referred to as the Extremum Consistency (EC) algorithm, to determine the optimal price to aspire for. The EC algorithm has successfully been used in handwritten signature verification for determining the maximum and minimum values in an input stream. The agent’s ability to inflate the price has been tested in a simulated marketplace and experimental results are presented.

References

  1. Hirschman, I. and Widder, D. (2005). The Convolution Transform. Dover Publications.
  2. Cliff, D. (1997). Minimal-intelligence agents for bargaining behaviours in market-based environments, Hewlett Packard Labs, Technical Report HPL-97-91.
  3. Dumas, M., Aldred, L. and Governatori, G. (2002). A probabilistic approach to automated bidding in alternative auctions, In Proceedings of the 11th International Conference on World Wide Web, 99-108. ACM Press.
  4. Gjerstad, S. and Dickhaut, J. (1998). Price formation in double auctions, Games and Economic Behavior, 22, 1- 29.
  5. Gode, D. and Sunder, S. (1993). Allocative efficiency of markets with zero intelligence traders: Market as a partial substitute for individual rationality, Journal of Political Economy, 101, 119-137.
  6. McCabe, A. and Trevathan, J. (2006). A new approach to avoiding the local extrema trap, In Proceedings of the 13th International Computational Techniques and Applications Conference.
  7. Rust, J., Miller, J. and Palmer, R. (1992). Behaviour of trading automata in a computerized double auction market, In The Double Auction Market: Institutions, Theories, and Evidence. Addison-Wesley.
  8. Schwartz, J. and Dobrzynski, J. (2002). 3 men are charged with fraud in 1 100 art auctions on eBay, The New York Times.
  9. Trevathan, J. and Read, W. (2006). RAS: a system for supporting research in online auctions, ACM Crossroads, 12.4, 23-30.
  10. Trevathan, J. and Read, W. (2007). A simple shill bidding agent, In Proceedings of the 4th International Conference on Information Technology - New Generations, 933-937.
  11. Wellman, M. and Wurman, P. (2003). The 2001 trading agent competition, Electronic Markets, 13.1, 4-12.
Download


Paper Citation


in Harvard Style

Trevathan J., McCabe A. and Read W. (2007). AN ADAPTIVE SHILL BIDDING AGENT . In Proceedings of the Second International Conference on e-Business - Volume 1: ICE-B, (ICETE 2007) ISBN 978-989-8111-11-1, pages 5-14. DOI: 10.5220/0002110600050014


in Bibtex Style

@conference{ice-b07,
author={Jarrod Trevathan and Alan McCabe and Wayne Read},
title={AN ADAPTIVE SHILL BIDDING AGENT},
booktitle={Proceedings of the Second International Conference on e-Business - Volume 1: ICE-B, (ICETE 2007)},
year={2007},
pages={5-14},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002110600050014},
isbn={978-989-8111-11-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on e-Business - Volume 1: ICE-B, (ICETE 2007)
TI - AN ADAPTIVE SHILL BIDDING AGENT
SN - 978-989-8111-11-1
AU - Trevathan J.
AU - McCabe A.
AU - Read W.
PY - 2007
SP - 5
EP - 14
DO - 10.5220/0002110600050014