infinite-horizon learning, and subjective expectations with Euler-equation learning. Under rational expectations, the model … necessitates of large, possibly unrealistically so, degrees of myopia. The same result persists under infinite-horizon learning …, given that agents are still remarkably far-sighted. But, under Euler-equation learning, the model can fit the data with only …

decision heuristics. Central to our survey is the question under which conditions a complex macro-system of interacting agents …

We designed four observational learning experiments to identify the key channels that, along with Bayes …-rational inferences, drive herd behavior. In Experiment 1, unobserved, whose actions remain private, learn from the public actions made in … observational learning accounts for the phenomenon of excessive herding, it captures well herd behavior with medium quality signals …

predictions about one-shot games and provides initial conditions for a theory of learning in repeated games. The learning theory … adds one parameter (to measure response sensitivity) and adjusts learning parameters for environmental change (e.g., old … comparable models like fictitious play and reinforcement learning. The teaching theory assumes some fraction of players realize …

The black box method was developed as an "asocial control" to allow for payoff-based learning while eliminating social … participants can unwittingly affect the learning of other participants. Here, we test a solution to this problem in a range of … no significant differences in rates of learning between the original and the computerised black box, therefore either …