We give a new approach in modeling the incomplete information in a buyer-seller game. We assume that the seller does not know the buyer's utility function at all. Usually the problem is solved by determining the Bayesian Nash equilibrium of the game, where it is assumed that the buyer's utility function has only some parameters unknown to the seller, and the seller knows the distribution of these parameters. Instead, we assume that the seller faces different types of buyers repeatedly, and the seller learns the buyers' preferences. We present an adjustment process that leads to Bayesian Nash equilibrium by using linear tariffs to extract enough information. This approach motivates the Bayesian Nash equilibrium of the buyer-seller game.
|Title of host publication||European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS)|
|Number of pages||5|
|Publication status||Published - 2004|
|MoE publication type||A4 Article in a conference publication|