False-Name-Proof Multi-unit Auction Protocol Utilizing Greedy Allocation Based on Approximate Evaluation Values
This paper presents a new false-name-proof multi-unit auction protocol called Greedy ALlocation (GAL) protocol. Internet auctions have become an integral part of Electronic Commerce and a promising field for applying agent and Artificial Intelligence technologies. Although the Internet provides an excellent infrastructure for executing auctions, the possibility of a new type of cheating called false-name bids has been pointed out. A false-name bid is a bid submitted under a fictitious name. A protocol called Iterative Reducing (IR) protocol has been developed for multi-unit auctions and has proven to be false-name-proof, i.e., using false-name bids is useless. For Internet auction protocols, being false-name-proof is important since identifying each participant on the Internet is virtually impossible.
One shortcoming of the IR protocol is that it requires the auctioneer to carefully pre-determine the reservation price for one unit. Our newly developed GAL protocol is easier to use than the IR, since the auctioneer does not need to set the reservation price nor any other parameters. The evaluation results show that the GAL protocol can obtain a social surplus that is very close to Pareto efficient. Furthermore, the obtained social surplus and seller’s revenue are much better than those of the IR protocol even if the reservation price is set optimally.
KeywordsMarginal Utility Reservation Price Combinatorial Auction Approximate Evaluation Social Surplus
Unable to display preview. Download preview PDF.
- 1.Sakurai, Y., Yokoo, M., Matsubara, S.: A limitation of the Generalized Vickrey Auction in Electronic Commerce: Robustness against false-name bids. In: Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99). (1999) 86–92Google Scholar
- 2.Yokoo, M., Sakurai, Y., Matsubara, S.: The effect of false-name declarations in mechanism design: Towards collective decision making on the Internet. In: Proceedings of the Twentieth International Conference on Distributed Computing Systems (ICDCS-2000). (2000) 146–153Google Scholar
- 3.Rasmusen, E.: Games and Information. Blackwell (1994)Google Scholar
- 4.Varian, H.R.: Economic mechanism design for computerized agents. In: Proceedings of the First Usenix Workshop on Electronic Commerce. (1995)Google Scholar
- 6.Yokoo, M., Sakurai, Y., Matsubara, S.: Robust multi-unit auction protocol against false-name bids. In: Proceedings of 17th International Joint Conference on Artificial Intelligence (IJCAI-2001). (2001) 1089–1094Google Scholar
- 7.Mas-Colell, A., Whinston, M.D., Green, J.R.: Microeconomic Theory. Oxford University Press (1995)Google Scholar
- 8.Sandholm, T.: An algorithm for optimal winner determination in combinatorial auction. In: Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99). (1999) 542–547Google Scholar
- 9.Lehmann, D., O’Callaghan, L.I., Shoham, Y.: Truth revelation in approximately efficient combinatorial auction. In: Proceedings of the First ACM Conference on Electronic Commerce (EC-99). (1999) 96–102Google Scholar
- 10.Shenker, S.: Fundamental design issues for the future internet. IEEE Journal on Selected Areas in Communication 13 (1995)Google Scholar
- 11.Ausubel, L., Cramton, P.: Demand reduction and inefficiency in multi-unit auctions. http://www.market-design.com/library.html (1998)
- 12.Cao, Z., Zegura, E.W.: Utility max-min: An application-oriented bandwidth allocation scheme. In: Proceedings of the Conference on Computer Communications (IEEE Infocom-99). (1999) 793–801Google Scholar
- 14.Fankhauser, G., Stiller, B., Vogtli, C., Plattner, B.: Reservation-based charging in an integrated services network. In: Proceedings of the 4th Institute for Operations Research and the Management Sciences Telecommunications Conference. (1998)Google Scholar