Learning in a black box

This chapter studies strategic behavior when agents have no information about the structure of the underlying game and they cannot observe other agents' actions or payoffs. Even when players have no such information, there are simple payoff-based learning rules that lead to Nash equilibrium in many types of games, as shown in Chapter 8. A key feature of these trial-and-error rules is that subjects search differently depending on whether their payoffs increase, stay constant, or decrease. This chapter analyzes learning behavior in a laboratory setting and finds strong empirical confirmation for these asymmetric search behaviors in the context of voluntary contribution games. By varying the amount of information, we show that these behaviors are also present even when subjects have full information about the game.