Learning Dynamics Based on Social Comparisond
Abstract
We study models of learning in games where agents with limited memory use social informationto decide when and how to change their play. When agents only observe the aggregate
distribution of payoffs and only recall information from the last period, we show that aggregate
play comes close to Nash equilibrium behavior for (generic) games, and that pure equilibria are
generally more stable than mixed equilibria. When agents observe not only the payoff distribution
of other agents but also the actions that led to those payoffs, and can remember this for
some time, the length of memory plays a key role. When agents’ memory is short, aggregate
play may not come close to Nash equilibrium, but it does so if the game satisfies a acyclicity
condition. When agents have sufficiently long memory their behavior comes close to Nash equilibrium
for generic games. However, unlike in the model where social information is solely about
how well other agents are doing, mixed equilibria can be favored over pure ones