affiliation-motivated individuals engaged in game-play. The first model captures learning by motivated agents during strategic …

opportunities to identify learning rules, since on networks (compared to, e.g., random matching) more rules differ in terms of their … information they consult before making their choices. We use these data to estimate learning types using finite mixture models … find that learning depends on network position. Participants in more complex environments (with more network neighbors …

understand better how subjects with different cognitive abilities learn differently, we estimate a structural model of learning … ability to that of character skills, and find that both cognition and personality affect behavior and learning. More agreeable …

learning process of individuals with different preference types (more and less pro-social) and coarse information regarding the …

. The results show that reinforcement learning leads to dynamics similar to those observed in standard public goods games … explained by reinforcement learning. According to our estimates, learning only accounts for 41 percent of the decay in …, differ strongly from the learning dynamics, while a learning model estimated from the limited information treatment tracks …