Optimal Bidding in Multiple Concurrent Auctions

In the face of multiple electronic sales sites, buyers can benefit from considering multiple opportunities and devising their purchase strategy to reduce risk and increase expected utility. However, human users cannot approach and rapidly monitor multiple sites. In particular, sites where prices change dynamically such as auction sites pose a major difficulty for human concurrent activity. Even without concurrency, the majority of human users do not have the ability or the resources to compute optimal purchase decisions. Such activities can be performed by computational agents. In this paper, we present mechanisms that allow agents to perform purchases on behalf of users. In particular, we devised methods that allow an agent that faces multiple dynamic sales sites to compute bids that optimize the expected utility of the user, or instead manage the winning probability of the purchase.