Learning and Equilibrium in Games

When and why will observed play in a game approximate an equilibrium, and what sort of equilibria will persist? To understand this, we study the long-run outcomes of rational non-equilibrium learning. In one-shot simultaneous-move games, steady states of such processes must be Nash equilibria, but this is not true in extensive- form games, where mistaken beliefs about opponents’ play and non-Nash outcomes can persist due to the tradeoff between exploration and exploitation. When players are patient, learning leads players to have the correct beliefs about the path of play and so to a subset of the Nash equilibria. Ongoing research analyzes this subset for the class of signalling games, which are known to have many implausible Nash equilibria.

日期：

2016年8月3日

演讲者：

Drew Fudenberg

所属机构：

MIT