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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References
An, N., Elmaghraby, W., Keskinocak, P.: Bidding strategies and their impact on revenues in combinatorial auctions. J. Rev. Pricing Manage. 3(4), 337–357 (2005)
Clearwater, S.: Market-Based Control: A Paradigm for Distributed Resource Allocation. World Scientific, Singapore (1996)
Cramton, P., Shoham, Y., Steinberg, R.: Combinatorial Auctions. MIT Press, Cambridge (2006)
de Vries, S., Vohra, R.: Combinatorial Auctions: A Survey. INFORMS. J. Comput. 15(3), 284–309 (2003)
Foster, I.: The Anatomy of the Grid: Enabling Scalable Virtual Organizations. In: Sakellariou, R., Keane, J.A., Gurd, J.R., Freeman, L. (eds.) Euro-Par 2001. LNCS, vol. 2150, p. 1. Springer, Heidelberg (2001)
Fujishima, Y., Leyton-Brown, K., Shoham, Y.: Taming the computational complexity of combinatorial auctions: Optimal and approximate approaches. In: IJCAI, pp. 548–553 (1999)
Galstyan, A., Kolar, S., Lerman, K.: Resource allocation games with changing resource capacities. In: AAMAS, pp. 145–152 (2003)
Parkes, D., Ungar, L.: Iterative combinatorial auctions: Theory and practice. In: AAAI, pp. 74–81 (2000)
Rassenti, S., Smith, V., Bulfin, R.: A combinatorial auction mechanism for airport time slot allocation. Be. J. of Econ. 13(2), 402–417 (1982)
Rothkopf, M., Pekec, A., Harstad, R.: Computationally Manageable Combinational Auctions. Manage. Sci. 44(8), 1131–1147 (1998)
Sandholm, T.: An implementation of the contract net protocol based on marginal cost calculations. In: AAAI, pp. 256–262 (1993)
Sandholm, T., Suri, S., Gilpin, A., Levine, D.: CABOB: A Fast Optimal Algorithm for Winner Determination in Combinatorial Auctions. Manage. Sci. 51(3), 374–390 (2005)
Schlegel, T., Kowalczyk, R.: Towards self-organising agent-based resource allocation in a multi-server environment. In: AAMAS, pp. 1–8. ACM, New York (2007)
Schwind, M., Stockheim, T., Gujo, O.: Agents’ Bidding Strategies in a Combinatorial Auction Controlled Grid Environment. In: TADA/AMEC, pp. 149–163 (2006)
Sui, X., Leung, H.F.: An Adaptive Bidding Strategy in Multi-Round Combinatorial Auctions for Resource Allocation. In: ICTAI. IEEE Computer Society, Los Alamitos (2008)
Zurel, E., Nisan, N.: An efficient approximate allocation algorithm for combinatorial auctions. In: ACM EC, pp. 125–136 (2001)
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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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