Learning by similarityweighted imitation in winnertakesall games Abstract   We study a simple model of similaritybased global cumulative imitation in symmetric games with large and ordered strategy sets and a salient winning player. We show that the learning model explains behavior well in both field and laboratory data from one such xe2x80x9cwinnertakesallxe2x80x9d game: the lowest unique positive integer game in which the player that chose the lowest number not chosen by anyone else wins a fixed prize. We corroborate this finding in three other winnertakesall games and discuss under what conditions the model may be applicable beyond this class of games. Theoretically, we show that global cumulative imitation without similarity weighting results in a version of the replicator dynamic in winnertakesall games.

Accuracy and Retaliation in Repeated Games with Imperfect Private Monitoring: Experiments Abstract   We experimentally examine repeated prisoneru0027s dilemma with random termination, in which monitoring is imperfect and private. Our estimation indicates that a significant proportion of the subjects follow generous titfortat strategies, which are stochastic extensions of titfortat. However, the observed retaliating policies are inconsistent with the generous titfortat equilibrium behavior. Showing inconsistent behavior, subjects with low accuracy do not tend to retaliate more than those with high accuracy. Furthermore, subjects with low accuracy tend to retaliate considerably with lesser strength than that predicted by the equilibrium theory, while subjects with high accuracy tend to retaliate with more strength than that predicted by the equilibrium theory, or with strength almost equivalent to it.