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Title: Revenue prediction in budget-constrained sequential auctions with complementarities (extended abstract)
Authors: Verwer, Sicco
Zhang, Yingqian #
Issue Date: 2012
Series Title: AAMAS 2012, The 11th International Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, June 4-8, Proceedings
Conference: International Conference on Autonomous Agents and Multiagent Systems edition:11 location:Valencia, Spain date:4-8 June 2012
Article number: Z6_9
Abstract: When multiple items are auctioned sequentially, the ordering of auctions plays an important role in the total revenue collected by the auctioneer. This is true especially with budget constrained bidders and the presence of complementarities among items. It is dicult to develop efficient algorithms for nding an optimal sequence of items. However, when historical data are available, it is possible to learn a model in order to predict the outcome of a given sequence. In this work, we show how to construct such a model, and
provide methods that fi nd a good sequence for a new set of items given the learned model. We develop an auction simulator and design several experiment settings to test the performance of the proposed methods.
URI: 
Publication status: published
KU Leuven publication type: IMa
Appears in Collections:Informatics Section
# (joint) last author

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