Abstract
Online auctions have become a popular method for business transactions. The variety of different auction rules, restrictions in supply or demand, and the agents’ combinatorial preferences for sets of goods, mean that realistic scenarios are very complex. Using game theory, we design trading strategies for participating in a single auction or group of similar auctions. A number of concerns need to be considered in order to account for all the relevant features of real-world auctions; these include: budget constraints, uncertainty in the value of the desired goods, the auction reserve prices, the bidders’ attitudes towards risk, purchasing multiple units, competition and spitefulness between bidders, the existence of multiple sources for each good. To design a realistic agent, it is necessary to analyze the multi-unit auctions in which a combination of these issues are present together and we have made significant progress towards this goal. Furthermore, we use a principled methodology, utilizing empirical evaluation, to combine these results into the design of agents capable of bidding in the general real-world scenarios.
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Vetsikas, I.A., Jennings, N.R. (2010). Designing Trading Agents for Real-World Auctions. In: Konstantopoulos, S., Perantonis, S., Karkaletsis, V., Spyropoulos, C.D., Vouros, G. (eds) Artificial Intelligence: Theories, Models and Applications. SETN 2010. Lecture Notes in Computer Science(), vol 6040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12842-4_31
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DOI: https://doi.org/10.1007/978-3-642-12842-4_31
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