Software agents are increasingly being used to represent humans in on-line auctions. Such agents have the advantages of being able to systematically monitor a wide variety of auctions and then make rapid decisions about what bids to place in what auctions. They can do this continuously and repetitively without losing concentration. Moreover, in complex multiple auction settings, agents may need to modify their behavior in one auction depending on what is happening in another. To provide a means of evaluating and comparing (benchmarking) research methods in this area, the Trading Agent Competition (TAC) was established. This competition involves a number of agents bidding against one another in a number of related auctions (operating different protocols) to purchase travel packages for customers. Against this background, this artcle describes the design, implementation and evaluation of our adaptive autonomous trading agent, SouthamptonTAC, one of the most successful participants in TAC 2002.