A Learning Approach to Auctions

Abstract

We analyze a repeated first-price auction in which the types of the players are determined before the first round. It is proved that if every player is using either a belief-based learning scheme with bounded recall or a generalized fictitious play learning scheme, then after sufficiently long time, the players' bids are in equilibrium in the one-shot auction in which the types are commonly known. Journal of Economic Literature Classification Numbers: C72, C73, D44, D83.