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A probabilistic approach to automated bidding in alternative auctions
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Source International World Wide Web Conference archive
Proceedings of the 11th international conference on World Wide Web table of contents
Honolulu, Hawaii, USA
SESSION: Auctions and E-commerce table of contents
Pages: 99 - 108  
Year of Publication: 2002
ISBN:1-58113-449-5
Authors
Marlon Dumas  Queensland University of Technology, Brisbane,Australia
Lachlan Aldred  Queensland University of Technology, Brisbane,Australia
Guido Governatori  University of Queensland, Brisbane,Australia
Arthur ter Hofstede  Queensland University of Technology, Brisbane,Australia
Nick Russell  Queensland University of Technology, Brisbane,Australia
Sponsors
ACM: Association for Computing Machinery
: WWW'02
Publisher
ACM  New York, NY, USA
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ABSTRACT

This paper presents an approach to develop bidding agents that participate in multiple alternative auctions, with the goal of obtaining an item at the lowest price. The approach consists of a prediction method and a planning algorithm. The prediction method exploits the history of past auctions in order to build probability functions capturing the belief that a bid of a given price may win a given auction. The planning algorithm computes the lowest price, such that by sequentially bidding in a subset of the relevant auctions, the agent can obtain the item at that price with an acceptable probability. The approach addresses the case where the auctions are for substitutable items with different values. Experimental results are reported, showing that the approach increases the payoff of their users and the welfare of the market.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Marlon Dumas: colleagues
Lachlan Aldred: colleagues
Guido Governatori: colleagues
Arthur ter Hofstede: colleagues
Nick Russell: colleagues