A. Greenwald, S. Lee and V. Naroditskiy (2009) "RoxyBot-06: Stochastic Prediction and Optimization in TAC Travel", Volume 36, pages 513-546

PDF | PostScript | doi:10.1613/jair.2904

In this paper, we describe our autonomous bidding agent, RoxyBot, who emerged victorious in the travel division of the 2006 Trading Agent Competition in a photo finish. At a high level, the design of many successful trading agents can be summarized as follows: (i) price prediction: build a model of market prices; and (ii) optimization: solve for an approximately optimal set of bids, given this model. To predict, RoxyBot builds a stochastic model of market prices by simulating simultaneous ascending auctions. To optimize, RoxyBot relies on the sample average approximation method, a stochastic optimization technique.

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