Iterative Combinatorial Auctions: Theory and Practice
| 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. |
| Full Text & Related Files: |
Parkes_Ungar_Iterative.pdf (158.3Kb; PDF) 
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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. |
| Other Sources: | http://www.eecs.harvard.edu/econcs/pubs/ibundle00.pdf |
| Terms of Use: | This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA |
| Citable link to this page: | http://nrs.harvard.edu/urn-3:HUL.InstRepos:4101023 |
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