Abstract
Combinatorial auction, where bidders can bid on bundles of items, has been the subject of increasing interest in recent years. Although much research work has been conducted on combinatorial auctions, most has focused on the winner determination problem. A largely unexplored area of research in combinatorial auctions is the design of bidding strategies. In this paper, we propose a new adaptive bidding strategy for combinatorial auction-based resource allocation problem in dynamic markets. A bidder adopting this strategy can adjust his profit margin constantly according to his bidding history, thus perceiving and responding to the dynamic market in a timely manner. Experiment results show that agents adaptive bidding strategy perform very well, even without any prior knowledge about the market.
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Sui, X., Leung, Hf. (2010). An Adaptive Bidding Strategy for Combinatorial Auction-Based Resource Allocation in Dynamic Markets. In: Zhang, BT., Orgun, M.A. (eds) PRICAI 2010: Trends in Artificial Intelligence. PRICAI 2010. Lecture Notes in Computer Science(), vol 6230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15246-7_47
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DOI: https://doi.org/10.1007/978-3-642-15246-7_47
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