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Journals ACM SIGecom Exchanges Volume 7 Issue 2

We describe a modular elicitation framework for iterative combinatorial auctions. The framework includes proxy agents, each of which can adopt an individualized bidding language to represent partial value information of a bidder. The framework leverages algorithms from query learning to elicit value information via bids as the auction progresses. The approach reduces the multi-agent elicitation problem to isolated, single-agent learning problems, with competitive equilibrium prices used to facilitate auction clearing even without complete learning.

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A modular framework for iterative combinatorial auctions

Lahaie, Séstien; Parkes, David C.
ACM SIGecom Exchanges , Volume 7 (2)
Association for Computing Machinery – Jun 1, 2008

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