Applying learning algorithms to preference elicitation
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Computational criticisms of the revelation principle
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Sequences of take-it-or-leave-it offers: near-optimal auctions without full valuation revelation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
ACM SIGecom Exchanges
On the optimization trade-offs of expanding ring search
IWDC'04 Proceedings of the 6th international conference on Distributed Computing
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Iterative auctions can reach an outcome before all bidders have revealed all their preference information. This can decrease costs associated with communication, deliberation, and loss of privacy. We propose an explicit cost model that is inspired by single-item Internet auctions, such as those taking place on auction sites (eBay) or via informal communication (craigslist, mailing lists). A nonzero bid comes at a cost to both the seller and the bidder, and the seller can send broadcast queries at a cost. Under this model, we study auctions that maximize the seller's profit (revenue minus seller cost). We consider multi-round Vickrey auctions (MVAs), in which the seller runs multiple Vickrey auctions, with decreasing reserve prices. We prove that restricting attention to this class is without loss of optimality, show how to compute an optimal MVA, and compare experimentally to some other natural MVAs. Among our findings are that (1) the expected total cost is bounded by a constant for arbitrarily many bidders, and (2) the optimal MVA and profit remain the same as long as the total bid cost is fixed, regardless of which portion of it belongs to the seller and which to the buyer.