  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.
