Iterative Combinatorial Auctions: Theory and Practice

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Iterative Combinatorial Auctions: Theory and Practice

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Title: Iterative Combinatorial Auctions: Theory and Practice
Author: Parkes, David C.; Ungar, Lyle H.

Note: Order does not necessarily reflect citation order of authors.

Citation: Parkes, David C., and Lyle H. Ungar. 2000. Iterative combinatorial auctions: Theory and practice. In Proceedings: Seventeenth National Conference on Artificial Intelligence (AAAI-2000): Twelfth Innovative Applications of Artificial Intelligence Conference (IAAI-2000), ed. American Association for Artificial Intelligence, 74-81. Menlo Park, C.A.: AAAI Press ; Cambridge, M.A.: MIT Press.
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Abstract: Combinatorial auctions, which allow agents to bid directly for bundles of resources, are necessary for optimal auction-based solutions to resource allocation problems with agents that have non-additive values for resources, such as distributed scheduling and task assignment problems. We introduce iBundle, the first iterative combinatorial auction that is optimal for a reasonable agent bidding strategy, in this case myopic best-response bidding. Its optimality is proved with a novel connection to primal-dual optimization theory. We demonstrate orders of magnitude performance improvements over the only other known optimal combinatorial auction, the Generalized Vickrey Auction.
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