Bidding Strategies for Trading Agents in Auction-Based Tournaments

Auction-based electronic commerce is an increasingly interesting domain for AI researchers. In this paper we present an attempt towards the construction of trading agents capable of competing in multi-agent auction markets by introducing both a formal and a more pragmatic approach to the design of bidding strategies for buyer agents in auction-based tournaments. Our formal view relies on possibilistic-based decision theory as the means of handling possibilistic uncertainty on the consequences of actions (bids) due to the lack of knowledge about the other agents' behaviour. For practical reasons we propose a two-fold method for decision making that does not require the evaluation of the whole set of alternative actions. This approach utilizes global (market-centered) information in a first step to come up with an initial set of potential bids. This set is subsequently refined in a second step by means of the possibilisitic decision model using individual (rival agent centered) information induced from a memory of cases composing the history of tournaments.