Rule learning posits that decision makers, rather than choosing over actions, choose over behavioral rules with different levels of sophistication. Rules are reinforced over time based on their historically observed payoffs in a given game. Past works on rule learning have shown that when...

We put forth a general theory of boundedly rational behavior and learning for symmetric normal-form games with unique symmetric Nash equilibria. A class of evidence-based behavioral rules is specified, which includes best-responding to a prior and Nash play. A player begins with initial...

How well do various learning models predict the dynamics of the population distribution of play in a variety of games? We measure and compare the in-sample and out-of-sample prediction performance of seven action-reinforcement learning models as well as Rule Learning for symmetric normal-form...

We test the population rule learning model for symmetric normal-form games, and strongly reject: (i) no rule learning, (ii) no diversity, and (iii) no sophisticated evidence. Further, trembles and herd behavior decline and level-2 behavior increases over time