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...

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...

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

This paper studies social learning and optimal pricing in the presence of location-based social networks, such as Foursquare. We provide an analytic model to resolve the following questions: (1) What is the optimal pricing strategy in location-based networks? (2) How do different pricing...

The increasing pervasiveness of social networks allows users to share purchase behaviors with their online friends. In the present study, we examine optimal pricing strategies of a monopolistic firm using an analytical model that accounts for behavioral observational learning in social networks....