learning. In repeat-choice situations, such learning brings value. If probabilities appear favorable (unfavorable), a choice …, decision makers often prove to be blind to the learning opportunities offered by uncertain probabilities. They forgo …, many make choices contrary to learning. Priming with optimal strategies offers little improvement. Such decision makers …

provide some necessary and some sufficient conditions for learning rules, that assume the agent has little prior and feedback …, Econometrica) who provide similar results for learning rules that seek higher expected payoffs. Our analysis reveals that a concern … for variance leads to quadratic transformations of payoffs to appear in the learning rule. …

We develop a dynamic model of opinion formation in social networks when the information required for learning a …

under both regimes. We also present a learning model that allows players to learn about the other playersʼ strategies and … the prior distribution of the senderʼs type. We show that this learning model accurately accounts for all main features of …

We study coordination in dynamic global games with private learning. Players choose whether and when to invest …

How do people learn? We assess, in a model-free manner, subjectsʼ belief dynamics in a two-armed bandit learning … unsuccessful choices, than “update up” following successful choices. The profits from following the estimated learning and decision …-rational Bayesian learning model, but comparable to the profits from alternative non-Bayesian learning models, including reinforcement …

human classification learning (Shepard et al., 1961). This allows us to evaluate the efficacy of CBDT as an account of human …