Computing Best-Response Strategies in Infinite Games of Incomplete Information

We describe an algorithm for computing best response strategies in a class of two-player infinite games of incomplete information, defined by payoffs piecewise linear in agents' types and actions, conditional on linear comparisons of agents' actions. We show that this class includes many well-known games including a variety of auctions and a novel allocation game. In some cases, the best-response algorithm can be iterated to compute Bayes-Nash equilibria. We demonstrate the efficiency of our approach on existing and new games.
Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004)