Bidding efficiently in repeated auctions with entry and observation costs

This paper introduces an efficient bidding strategy for budget-constrained buyers in repeated auctions with entry fees. We present a general algorithm that is applicable to distributed resource allocation. The game is modeled on an economically reasonable assumption [1] according to which any player can participate in an auction after paying for information about the value of the auctioned item, and for the preparation of his bid. We address learning by each bidder of an optimal participation strategy for spending his budget profitably, based on the history of his successes and failures in past transactions. Players' transient and long-term attitudes are illustrated in a symmetric Bayesian equilibrium of a market-based network resource allocation problem.